Solution of the Fuzzy Equation A + X = B Using the Method of Superimposition

Size: px
Start display at page:

Download "Solution of the Fuzzy Equation A + X = B Using the Method of Superimposition"

Transcription

1 Appled Mathematcs do:046/am0844 Publshed Ole August 0 ( Soluto of the Fuzzy Equato A + X = B Usg the Method of Supermposto Fokrul Alom Mazarbhuya Ajaa Kakot Mahata Hemata K Baruah Departmet of Computer Scece College of Computer Scece Kg Khald Uersty Abha Saud Araba Departmet of Computer Scece Gauhat Uersty Assam Ida Departmet of Statstcs Gauhat Uersty Assam Ida E-mal: fokrul_005@yahoocom ajaagu@yahooco hemata_bh@yahoocom Receed March 7 0; resed Jue 0; accepted July 0 Abstract Fuzzy equatos ere soled by usg dfferet stadard methods Oe of the ell-ko methods s the method of -cut The method of supermposto of sets has bee used to defe arthmetc operatos of fuzzy umbers I ths artcle t has bee sho that the fuzzy equato A X B A X B are fuzzy umbers ca be soled by usg the method of supermposto of sets It has also bee sho that the method ges same result as the method of -cut Keyords: Fuzzy Number Possblty Dstrbuto Probablty Dstrbuto Sural Fucto Supermposto of Sets Supermposto of Iterals -Cut Method Itroducto Fuzzy equatos ere estgated by Dubos ad Prade [] Sachez [] put forard a soluto of fuzzy equato by usg exteded operatos Accordgly arous researchers hae proposed dfferet methods for solg the fuzzy equatos [see eg Buckley [] Wasosk [4] Baco ad Letter [5] After ths a lot research papers hae appeared proposg solutos of arous types of fuzzy equatos z algebrac fuzzy equatos a system of fuzzy lear equatos smultaeous lear equatos th fuzzy coeffcets etc usg dfferet methods ([see eg Jag [6] Buckley ad Qu [7] Kaaguch ad Da-Te [8] Zhao ad Gobd [9] Wag ad Ha [0] Klr ad Yua [] soled the fuzzy equatos A X B A X ad B are fuzzy umbers by usg the method of -cut Mazarbhuya et al [] defed the arthmetc operatos z addto ad subtracto of fuzzy umbers th out usg the method of -cuts e usg a method called supermposto of sets troduced by Baruah [] I ths artcle e ould put forard a procedure of solg a fuzzy equato A X B thout utlsg the stadard methods Our method s based o the operato of supermposto of sets It ll be sho ths artcle that our method for the soluto of equato A X B ges same result as ge by the method of -cut The paper s orgased as follos I Secto e dscuss about the deftos ad otatos used ths artcle I Secto e dscuss the soluto of fuzzy equato by -cut method I Secto 4 e dscuss about equ-fuzzy teral arthmetc I Secto 5 e dscuss our proposed method of soluto A X B I Secto 6 e ge bref cocluso of the ork ad les for future ork Deftos ad Notatos We frst ree certa stadard deftos Let E be a set ad let x be a elemet E The a fuzzy subset A of E s characterzed by A xax ; x E A x s the grade of membershp of x A A(x s commoly called the fuzzy membershp fucto of the fuzzy set A For a ordary set A(x s ether 0 or hle for a fuzzy set A x 0 A fuzzy set A s sad be ormal f ts membershp fucto Ax s uty for at least oe x E A -cut A of a fuzzy set A s a ordary set of elemets th membershp ot less tha for 0 Ths meas A xe; A x Copyrght 0 ScRes

2 040 F A MAZARBHUIYA ET AL A fuzzy set s sad to be coex f all ts -cuts are coex sets (see eg [4] A fuzzy umber s a coex ormal fuzzy set A defed o the real le such that A(x s pecese cotuous The support of a fuzzy set A s deoted by sup p A ad s defed as the set of elemets th membershp ozero e sup p A xe; A x 0 A fuzzy umber A deoted by a trad [abc] such that Aa 0 Ac ad Ab A x for x [ ab ] s called the left referece fucto ad for x [] bc s called rght referece fucto The left referece fucto s rght cotuous mootoe ad o-decreasg as the rght referece fucto s left cotuous mootoe ad o-creasg The aboe defto of a fuzzy umber s called L-R fuzzy umber [5] We ould call a fuzzy set A ( oer the support A equ-fuzzy f all elemets of A ( are th membershp 0 The operato of supermposto S of equ-fuzzy sets A ( ad B ( s defed as [] B A B A SB AAB AB 0 ad the operato + stads for uo of dsjot sets fuzzy or otherse The arthmetc operato usg the method of -cut o to fuzzy umbers A ad B s defed by the formula A* B A* A B are -cuts of A ad B (0] ad * s the arthmetc operato o A ad B I the case of dso 0 B for ay (0] The resultg fuzzy umber A* B s expressed as A* B A* B (see eg[] ( Soluto of the Fuzzy Equato AX B by Usg the Method of -Cut For ay (0] Let A a a B b b ad X x x deote respectely the -cuts of A B ad X the ge equato (see eg Klr ad Yua [] The the ge equato has a soluto f a oly f b a b a for eery (0] ad b a b a b a b a Property esures that the teral equato A X B B has a soluto hch s X b a b a Property esures that the soluto of the teral equatos for ad are ested e f the X X f a soluto X exsts for eery (0] ad property s satsfed the by ( the soluto X of the fuzzy equato s X X ( X x X x [0] 4 Equ-Fuzzy Iteral Arthmetc The usual teral arthmetc ca be geeralzed for equ-fuzzy terals If A [ a b] ad B [ a b] e deote teral addto ad teral subtracto as A( B [ a a b b ] ad A( B a b a b Accordgly ( ( ( A ( B aa b b ( ( ( A ( B ab a b Let o ( ( be the ordered alues of ascedg magtude The a b Sa b ( c d Sc d (/ (/ (/ (/ a a a b b b (/ ( (/ ( ( ( ( ( ( ( c c c d d d (/ ( (/ ( ( ( ( ( ( (/ a( c( a( c ( a b d b d ( ( ( ( (/ a b c d Smlarly c b d ( ( ( ( a b Sa b ( c d Sc d (/ (/ (/ (/ (/ ( (/ a( a ( a( b ( b( b ( ( (/ ( (/ c( c ( c( d ( d( d ( (/ a( d( a( d ( a b c b c ( ( ( ( (/ d b c ( ( ( ( ( ( ( (4 Copyrght 0 ScRes

3 F A MAZARBHUIYA ET AL 04 I the ext secto e shall use ( ad (4 to fd the soluto X of the fuzzy equato A X B 5 Soluto of the Fuzzy Equato AX B by Usg the Method of Supermposto Let a a a are sample realsatos from the uform populato [ u ] ad b b b are sample realsatos from the uform populato [ ] We deote G a b as the supermpostos of equfuzzy terals [ a b ]; th membershp (/ e (/ (/ (/ G a b a b S a b S S a b (/ (/ ( ( ( ( a a a a (( / ( a( a ( a( b ( (/ (/ b( b ( b( b ( (/ b( b ( Ha b (say (5 a a a are ordered alues of a a a ad b b b are ordered alues of b b b ascedg magtude Here [ a b] From (5 e get the membershp fuctos are the combato of emprcal probablty dstrbuto fucto ad complemetary probablty dstrbuto fucto respectely as ad 0 x a( r x a( r x a ( r x a( x b( r x b( r xb ( r 0 x b( It s ko that the Gleko-Catell lemma of Order Statstcs [6] states that the mathematcal expectato of emprcal dstrbuto fucto s the theoretcal probablty dstrbuto fucto ad that of emprcal complemetary probablty dstrbuto the theoretcal sural fucto Thus x E x P u ad E x P x (6 0 x u x u Pu x u x x u s the uform probablty dstrbuto fucto o [ u ] ad 0 x x P x x x s the uform probablty dstrbuto fucto o [ ] From (5 usg (6 e get the membershp grades Ga b hch s othg but H ab ca be estmated by the membershp fucto 0 xu x x u x x A x u x u A [ u ] s a fuzzy umber Aga let x x x are sample realsatos from the uform populato [ u ] ad y y y are sample realsatos from the uform populato [ ] We deote G x y as the supermposto of equfuzzy terals [ x y ] ; th membershp (/ e (/ (/ (/ G x y x y S x y S S x y (/ (/ x( x ( x( x ( (( / ( (/ x( x ( x( y ( y( y ( (/ (/ y( y ( y( y ( Hx y (8 x x x are the ordered alues of x x x ad y y y are the ordered alues of y y y ascedg order of magtude ad here (7 Copyrght 0 ScRes

4 04 F A MAZARBHUIYA ET AL x y Here the emprcal probablty dstrbuto fucto ad emprcal complemetary dstrbuto fucto are respectely ge by ad ad 0 x x( r x x( r x x ( r x x( 0 x y( r 4 x y( r x y ( r x y( By Gleko Catell lemma of order statstcs e get E x P u x E x P x 4 (9 0 x u x u P u x u x u x s the uform probablty dstrbuto fucto o [u ] Ad 0 x x P x x x s the uform probablty dstrbuto fucto o [ ] From (8 usg (9 e get the membershp grades G(xy hch s othg but H xy ca be estmated by the membershp fucto 0 xu x x u x x X x u x u her e X u [ ] It as assumed that x y s also a fuzzy umber Aga let c c c are sample realsatos from the uform populato [ u ] ad d d d are sample realsatos from the uform populato [ ] We deote G c d as the supermposto of equ- fuzzy terals [ c d ]; th membershp (/ e (/ (/ (/ S c d S c d G c d c d S (/ (/ c ( c( c( c ( (( / ( c( c ( c( d ( (0 c c c are the ordered alues of c c c ad d d d are the ordered alues of d d d ascedg order of magtude ad here c d (/ (/ d( d ( d( d ( d d Hc d ( ( (/ Here the emprcal probablty dstrbuto fucto ad emprcal complemetary dstrbuto fucto are respectely ge by ad 0 x c( r x c x c x c( 5 ( r ( r 0 x d( r x d x d x d( 6 ( r ( r By Gleko Catell lemma of order statstcs e get ad x E x P u 5 E x P 6 x ( Copyrght 0 ScRes

5 F A MAZARBHUIYA ET AL 04 0 x u x u P x u x u x s the uform probablty dstrbuto fucto o [u ] ad 0 x x P x x x s the uform probablty dstrbuto fucto o [ ] From (0 usg ( e get the membershp grades Gc d hch s othg but H cd ca be estmated by the membershp fucto It as assumed that 0 xu x x u B x u x u B [ u ] x x s a fuzzy umber c d The ge equato ca be rtte as Replacg the alues of G a b G x y ad Gc d ad usg the equ-f uzzy teral arthm etc e get e a x a x G a b ( G x y G c d (/ (/ a x a x ( ( ( ( ( ( ( ( a( r x( r a( r x ( r (( / a( x( a( x ( ] ( (/ a( x( b( y( b( y( b( y ( (/ b y b y ( ( ( ( b y b y ( ( ( ( H a x b y H c d (/ (( r/ Usg the equalty of equ-fuzzy terals e get a x c ad b y d ; hch ges x c a ad y d b ; Ths mples (/ (/ x( x ( x( x ( (( r/ (( / x( r x ( r x( x ( ( (/ x( y ( y( y ( (/ (/ y( y ( y( y ( (/ (/ c ( a( c( a( c( a( c( a( (( r/ c( r a( r c( r a ( r (( / c( a( c a( ( ( (/ c d b ( ( d b a d b d b ( ( ( ( ( ( d ( r ( r ( r ( r d b d b ( ( ( ( b (/ (( r/ ( The left sde of the detty ( s Gx y hose membershp fucto X x s estmated by (9 ad from the rght sde e get the emprcal probablty dstrbuto fucto ad sural fucto as ad 0 xc( a( 7 r x c( r a( r xc( r a r x c( a( 0 x d( b( r x d b x d b r x d( b( 8 ( r ( r ( r ( By Gleko Catell Lemma of order Statstcs ad P E x u u x 7 E x P 8 x ( 0 xu u xu u Pu u x u u x u u x s the uform probablty dstrbuto fucto o [ u u ad ] ( Copyrght 0 ScRes

6 044 F A MAZARBHUIYA ET AL 0 x x Pu u x x x s the uform probablty dstrbuto fucto o [ ] From ( e get the soluto of the equato A X B as X u u (4 0 xu u x xu u X x u u x u u x x Obously u B A X u u u From the Equato (4 e get X u u s a fuzzy umber hose -cut s ge by X u u u u hch s the soluto of A X B Obously [0] X u u u u that s smlar to the Equato ( Thus e ca coclude that the method of supermposto ges the same result as ge by the method of -cut 6 Cocluso ad Les for Future Works I ths artcle e hae preseted a e method of solg fuzzy equato A X B The method s based o the set supermposto operato The set supermpos- has bee used to defe the arthmetc op- to method eratos o fuzzy umbers It has bee foud that the arthmetc operato based o set supermposto operato ges the same result as ge by other stadard method z the method of -cut I ths artcle e hae sho that our method of soluto of fuzzy equato A X B ges the smlar results a s ge by other stadard methods I future e ould lke sole other kd of fuzzy equato amely fuzzy dfferetal equategral equato etc usg same to fuzzy method 7 Refereces [] D Dubos ad H Prade Fuzzy Set Theoretc Dffereces ad Iclusos ad Ther Use The aalyss of Fuzzy Equatos Cotrol Cyber (Warsha Vol 984 pp 9-46 [] E Sachez Soluto of Fuzzy Equatos th Exteded Operatos Fuzzy Sets ad Systems Vol 984 pp 7-48 do:006/065-04( x [] J J Buckley Solg Fuzzy Equatos Fuzzy Sets ad Systems Vol 50 No 99 pp -4 do:006/065-04(99099-e [4] J Wasosk O Solutos to Fuzzy Equatos Cotrol ad Cyber Vol pp [5] L Baco ad A Letter Equato th Fuzzy Numbers Iformato Sceces Vol 47 No 989 pp 6-76 [6] H Jag The Approach to Solg Smultaeous Lear Equatos That Coeffcets Are Fuzzy Numbers Joural of Natoal Uersty of Defece Techology (Chese Vol 986 pp 96-0 [7] J J Buckley ad Y Qu Solg Lear ad Quadratc Equatos Fuzzy Sets ad Systems Vol 8 No 990 pp do: 006/065-04( R [8] M F Kaaguch ad T Da-Te A Calculato Method for Solg Fuzzy Arthmetc Equato th Tragular Norms Proceedgs of d IEEE Iteratoal Coferece o Fuzzy Systems (FUZZY-IEEE Sa Fracsco 99 pp [9] R Zhao ad R God Solutos of Algebrac Equatos Iolg Geeralsed Fuzzy Number Iformato Sceces Vol pp 99-4 do:006/ (9900-o [0] X Wag ad M Ha Solg a System of Fuzzy Lear Equatos I: M Delgado J Kacpryzyk J L Verdegay ad A Vla Eds Fuzzy Optmsato: Recet Adaces Physca-Verlag Heldelberg 994 pp 0-08 [] G J Klr ad B Yua Fuzzy Sets ad Fuzzy Logc Theory ad Applcatos Pretce Hall of Ida Pt Ltd Delh 00 [] F A Mazarrbhuya A K Mahata ad H K Baruah Fuzzy Arthmetc thout Usg the Method of -Cuts Bullet of Pure ad Appled Sceces Vol E No 00 pp [] H K Baruah Set Supermposto ad Its Applcato to the Theory of Fuzzy sets Joural of Assam Scece Copyrght 0 ScRes

7 F A MAZARBHUIYA ET AL 045 Socety Vol 0 No pp 5- [4] G Q Che S C Lee ad S H Yu Ede Applc ato of Fuzzy Set Theory to Ecoomcs I: P P Wag Ed Adaces Fuzzy Sets Possblty Theory ad Applcatos Pleum Press Ne York 98 pp [5] D Dubos ad H Prade Rakg Fuzzy Numbers the Settg of Possblty Theory Iformato Scece Vol 0 No 98 pp 8-4 do:006/ ( [6] M Loee Probablty Theory Sprger Verlag Ne York 977 Copyrght 0 ScRes

On Eccentricity Sum Eigenvalue and Eccentricity Sum Energy of a Graph

On Eccentricity Sum Eigenvalue and Eccentricity Sum Energy of a Graph Aals of Pure ad Appled Mathematcs Vol. 3, No., 7, -3 ISSN: 79-87X (P, 79-888(ole Publshed o 3 March 7 www.researchmathsc.org DOI: http://dx.do.org/.7/apam.3a Aals of O Eccetrcty Sum Egealue ad Eccetrcty

More information

Analyzing Fuzzy System Reliability Using Vague Set Theory

Analyzing Fuzzy System Reliability Using Vague Set Theory Iteratoal Joural of Appled Scece ad Egeerg 2003., : 82-88 Aalyzg Fuzzy System Relablty sg Vague Set Theory Shy-Mg Che Departmet of Computer Scece ad Iformato Egeerg, Natoal Tawa versty of Scece ad Techology,

More information

MAX-MIN AND MIN-MAX VALUES OF VARIOUS MEASURES OF FUZZY DIVERGENCE

MAX-MIN AND MIN-MAX VALUES OF VARIOUS MEASURES OF FUZZY DIVERGENCE merca Jr of Mathematcs ad Sceces Vol, No,(Jauary 0) Copyrght Md Reader Publcatos wwwjouralshubcom MX-MIN ND MIN-MX VLUES OF VRIOUS MESURES OF FUZZY DIVERGENCE RKTul Departmet of Mathematcs SSM College

More information

Analysis of Lagrange Interpolation Formula

Analysis of Lagrange Interpolation Formula P IJISET - Iteratoal Joural of Iovatve Scece, Egeerg & Techology, Vol. Issue, December 4. www.jset.com ISS 348 7968 Aalyss of Lagrage Iterpolato Formula Vjay Dahya PDepartmet of MathematcsMaharaja Surajmal

More information

Generalization of the Dissimilarity Measure of Fuzzy Sets

Generalization of the Dissimilarity Measure of Fuzzy Sets Iteratoal Mathematcal Forum 2 2007 o. 68 3395-3400 Geeralzato of the Dssmlarty Measure of Fuzzy Sets Faramarz Faghh Boformatcs Laboratory Naobotechology Research Ceter vesa Research Isttute CECR Tehra

More information

Non-uniform Turán-type problems

Non-uniform Turán-type problems Joural of Combatoral Theory, Seres A 111 2005 106 110 wwwelsevercomlocatecta No-uform Turá-type problems DhruvMubay 1, Y Zhao 2 Departmet of Mathematcs, Statstcs, ad Computer Scece, Uversty of Illos at

More information

Further Results on Pair Sum Labeling of Trees

Further Results on Pair Sum Labeling of Trees Appled Mathematcs 0 70-7 do:046/am0077 Publshed Ole October 0 (http://wwwscrporg/joural/am) Further Results o Par Sum Labelg of Trees Abstract Raja Poraj Jeyaraj Vjaya Xaver Parthpa Departmet of Mathematcs

More information

Q-analogue of a Linear Transformation Preserving Log-concavity

Q-analogue of a Linear Transformation Preserving Log-concavity Iteratoal Joural of Algebra, Vol. 1, 2007, o. 2, 87-94 Q-aalogue of a Lear Trasformato Preservg Log-cocavty Daozhog Luo Departmet of Mathematcs, Huaqao Uversty Quazhou, Fua 362021, P. R. Cha ldzblue@163.com

More information

A New Method for Solving Fuzzy Linear. Programming by Solving Linear Programming

A New Method for Solving Fuzzy Linear. Programming by Solving Linear Programming ppled Matheatcal Sceces Vol 008 o 50 7-80 New Method for Solvg Fuzzy Lear Prograg by Solvg Lear Prograg S H Nasser a Departet of Matheatcs Faculty of Basc Sceces Mazadara Uversty Babolsar Ira b The Research

More information

The Lie Algebra of Smooth Sections of a T-bundle

The Lie Algebra of Smooth Sections of a T-bundle IST Iteratoal Joural of Egeerg Scece, Vol 7, No3-4, 6, Page 8-85 The Le Algera of Smooth Sectos of a T-udle Nadafhah ad H R Salm oghaddam Astract: I ths artcle, we geeralze the cocept of the Le algera

More information

A Remark on the Uniform Convergence of Some Sequences of Functions

A Remark on the Uniform Convergence of Some Sequences of Functions Advaces Pure Mathematcs 05 5 57-533 Publshed Ole July 05 ScRes. http://www.scrp.org/joural/apm http://dx.do.org/0.436/apm.05.59048 A Remark o the Uform Covergece of Some Sequeces of Fuctos Guy Degla Isttut

More information

Complete Convergence and Some Maximal Inequalities for Weighted Sums of Random Variables

Complete Convergence and Some Maximal Inequalities for Weighted Sums of Random Variables Joural of Sceces, Islamc Republc of Ira 8(4): -6 (007) Uversty of Tehra, ISSN 06-04 http://sceces.ut.ac.r Complete Covergece ad Some Maxmal Iequaltes for Weghted Sums of Radom Varables M. Am,,* H.R. Nl

More information

Solution of General Dual Fuzzy Linear Systems. Using ABS Algorithm

Solution of General Dual Fuzzy Linear Systems. Using ABS Algorithm Appled Mathematcal Sceces, Vol 6, 0, o 4, 63-7 Soluto of Geeral Dual Fuzzy Lear Systems Usg ABS Algorthm M A Farborz Aragh * ad M M ossezadeh Departmet of Mathematcs, Islamc Azad Uversty Cetral ehra Brach,

More information

Research Article A New Iterative Method for Common Fixed Points of a Finite Family of Nonexpansive Mappings

Research Article A New Iterative Method for Common Fixed Points of a Finite Family of Nonexpansive Mappings Hdaw Publshg Corporato Iteratoal Joural of Mathematcs ad Mathematcal Sceces Volume 009, Artcle ID 391839, 9 pages do:10.1155/009/391839 Research Artcle A New Iteratve Method for Commo Fxed Pots of a Fte

More information

Chapter 5 Properties of a Random Sample

Chapter 5 Properties of a Random Sample Lecture 6 o BST 63: Statstcal Theory I Ku Zhag, /0/008 Revew for the prevous lecture Cocepts: t-dstrbuto, F-dstrbuto Theorems: Dstrbutos of sample mea ad sample varace, relatoshp betwee sample mea ad sample

More information

9 U-STATISTICS. Eh =(m!) 1 Eh(X (1),..., X (m ) ) i.i.d

9 U-STATISTICS. Eh =(m!) 1 Eh(X (1),..., X (m ) ) i.i.d 9 U-STATISTICS Suppose,,..., are P P..d. wth CDF F. Our goal s to estmate the expectato t (P)=Eh(,,..., m ). Note that ths expectato requres more tha oe cotrast to E, E, or Eh( ). Oe example s E or P((,

More information

Chapter 8: Statistical Analysis of Simulated Data

Chapter 8: Statistical Analysis of Simulated Data Marquette Uversty MSCS600 Chapter 8: Statstcal Aalyss of Smulated Data Dael B. Rowe, Ph.D. Departmet of Mathematcs, Statstcs, ad Computer Scece Copyrght 08 by Marquette Uversty MSCS600 Ageda 8. The Sample

More information

Solving Interval and Fuzzy Multi Objective. Linear Programming Problem. by Necessarily Efficiency Points

Solving Interval and Fuzzy Multi Objective. Linear Programming Problem. by Necessarily Efficiency Points Iteratoal Mathematcal Forum, 3, 2008, o. 3, 99-06 Solvg Iterval ad Fuzzy Mult Obectve ear Programmg Problem by Necessarly Effcecy Pots Hassa Mshmast Neh ad Marzeh Aleghad Mathematcs Departmet, Faculty

More information

Module 7: Probability and Statistics

Module 7: Probability and Statistics Lecture 4: Goodess of ft tests. Itroducto Module 7: Probablty ad Statstcs I the prevous two lectures, the cocepts, steps ad applcatos of Hypotheses testg were dscussed. Hypotheses testg may be used to

More information

Nonlinear Piecewise-Defined Difference Equations with Reciprocal Quadratic Terms

Nonlinear Piecewise-Defined Difference Equations with Reciprocal Quadratic Terms Joural of Matematcs ad Statstcs Orgal Researc Paper Nolear Pecewse-Defed Dfferece Equatos wt Recprocal Quadratc Terms Ramada Sabra ad Saleem Safq Al-Asab Departmet of Matematcs, Faculty of Scece, Jaza

More information

4 Inner Product Spaces

4 Inner Product Spaces 11.MH1 LINEAR ALGEBRA Summary Notes 4 Ier Product Spaces Ier product s the abstracto to geeral vector spaces of the famlar dea of the scalar product of two vectors or 3. I what follows, keep these key

More information

Research Article Some Strong Limit Theorems for Weighted Product Sums of ρ-mixing Sequences of Random Variables

Research Article Some Strong Limit Theorems for Weighted Product Sums of ρ-mixing Sequences of Random Variables Hdaw Publshg Corporato Joural of Iequaltes ad Applcatos Volume 2009, Artcle ID 174768, 10 pages do:10.1155/2009/174768 Research Artcle Some Strog Lmt Theorems for Weghted Product Sums of ρ-mxg Sequeces

More information

Lecture 12 APPROXIMATION OF FIRST ORDER DERIVATIVES

Lecture 12 APPROXIMATION OF FIRST ORDER DERIVATIVES FDM: Appromato of Frst Order Dervatves Lecture APPROXIMATION OF FIRST ORDER DERIVATIVES. INTRODUCTION Covectve term coservato equatos volve frst order dervatves. The smplest possble approach for dscretzato

More information

Decomposition of Hadamard Matrices

Decomposition of Hadamard Matrices Chapter 7 Decomposto of Hadamard Matrces We hae see Chapter that Hadamard s orgal costructo of Hadamard matrces states that the Kroecer product of Hadamard matrces of orders m ad s a Hadamard matrx of

More information

THE PROBABILISTIC STABILITY FOR THE GAMMA FUNCTIONAL EQUATION

THE PROBABILISTIC STABILITY FOR THE GAMMA FUNCTIONAL EQUATION Joural of Scece ad Arts Year 12, No. 3(2), pp. 297-32, 212 ORIGINAL AER THE ROBABILISTIC STABILITY FOR THE GAMMA FUNCTIONAL EQUATION DOREL MIHET 1, CLAUDIA ZAHARIA 1 Mauscrpt receved: 3.6.212; Accepted

More information

TWO NEW WEIGHTED MEASURES OF FUZZY ENTROPY AND THEIR PROPERTIES

TWO NEW WEIGHTED MEASURES OF FUZZY ENTROPY AND THEIR PROPERTIES merca. Jr. of Mathematcs ad Sceces Vol., No.,(Jauary 0) Copyrght Md Reader Publcatos www.jouralshub.com TWO NEW WEIGTED MESURES OF FUZZY ENTROPY ND TEIR PROPERTIES R.K.Tul Departmet of Mathematcs S.S.M.

More information

Generalized Minimum Perpendicular Distance Square Method of Estimation

Generalized Minimum Perpendicular Distance Square Method of Estimation Appled Mathematcs,, 3, 945-949 http://dx.do.org/.436/am..366 Publshed Ole December (http://.scrp.org/joural/am) Geeralzed Mmum Perpedcular Dstace Square Method of Estmato Rezaul Karm, Morshed Alam, M.

More information

Chapter 9 Jordan Block Matrices

Chapter 9 Jordan Block Matrices Chapter 9 Jorda Block atrces I ths chapter we wll solve the followg problem. Gve a lear operator T fd a bass R of F such that the matrx R (T) s as smple as possble. f course smple s a matter of taste.

More information

On Submanifolds of an Almost r-paracontact Riemannian Manifold Endowed with a Quarter Symmetric Metric Connection

On Submanifolds of an Almost r-paracontact Riemannian Manifold Endowed with a Quarter Symmetric Metric Connection Theoretcal Mathematcs & Applcatos vol. 4 o. 4 04-7 ISS: 79-9687 prt 79-9709 ole Scepress Ltd 04 O Submafolds of a Almost r-paracotact emaa Mafold Edowed wth a Quarter Symmetrc Metrc Coecto Mob Ahmad Abdullah.

More information

Some Statistical Inferences on the Records Weibull Distribution Using Shannon Entropy and Renyi Entropy

Some Statistical Inferences on the Records Weibull Distribution Using Shannon Entropy and Renyi Entropy OPEN ACCESS Coferece Proceedgs Paper Etropy www.scforum.et/coferece/ecea- Some Statstcal Ifereces o the Records Webull Dstrbuto Usg Shao Etropy ad Rey Etropy Gholamhosse Yar, Rezva Rezae * School of Mathematcs,

More information

Entropy ISSN by MDPI

Entropy ISSN by MDPI Etropy 2003, 5, 233-238 Etropy ISSN 1099-4300 2003 by MDPI www.mdp.org/etropy O the Measure Etropy of Addtve Cellular Automata Hasa Aı Arts ad Sceces Faculty, Departmet of Mathematcs, Harra Uversty; 63100,

More information

Part 4b Asymptotic Results for MRR2 using PRESS. Recall that the PRESS statistic is a special type of cross validation procedure (see Allen (1971))

Part 4b Asymptotic Results for MRR2 using PRESS. Recall that the PRESS statistic is a special type of cross validation procedure (see Allen (1971)) art 4b Asymptotc Results for MRR usg RESS Recall that the RESS statstc s a specal type of cross valdato procedure (see Alle (97)) partcular to the regresso problem ad volves fdg Y $,, the estmate at the

More information

Double Dominating Energy of Some Graphs

Double Dominating Energy of Some Graphs Iter. J. Fuzzy Mathematcal Archve Vol. 4, No., 04, -7 ISSN: 30 34 (P), 30 350 (ole) Publshed o 5 March 04 www.researchmathsc.org Iteratoal Joural of V.Kaladev ad G.Sharmla Dev P.G & Research Departmet

More information

The Arithmetic-Geometric mean inequality in an external formula. Yuki Seo. October 23, 2012

The Arithmetic-Geometric mean inequality in an external formula. Yuki Seo. October 23, 2012 Sc. Math. Japocae Vol. 00, No. 0 0000, 000 000 1 The Arthmetc-Geometrc mea equalty a exteral formula Yuk Seo October 23, 2012 Abstract. The classcal Jese equalty ad ts reverse are dscussed by meas of terally

More information

The Necessarily Efficient Point Method for Interval Molp Problems

The Necessarily Efficient Point Method for Interval Molp Problems ISS 6-69 Eglad K Joural of Iformato ad omputg Scece Vol. o. 9 pp. - The ecessarly Effcet Pot Method for Iterval Molp Problems Hassa Mshmast eh ad Marzeh Alezhad + Mathematcs Departmet versty of Ssta ad

More information

X ε ) = 0, or equivalently, lim

X ε ) = 0, or equivalently, lim Revew for the prevous lecture Cocepts: order statstcs Theorems: Dstrbutos of order statstcs Examples: How to get the dstrbuto of order statstcs Chapter 5 Propertes of a Radom Sample Secto 55 Covergece

More information

The internal structure of natural numbers, one method for the definition of large prime numbers, and a factorization test

The internal structure of natural numbers, one method for the definition of large prime numbers, and a factorization test Fal verso The teral structure of atural umbers oe method for the defto of large prme umbers ad a factorzato test Emmaul Maousos APM Isttute for the Advacemet of Physcs ad Mathematcs 3 Poulou str. 53 Athes

More information

Multivariate Transformation of Variables and Maximum Likelihood Estimation

Multivariate Transformation of Variables and Maximum Likelihood Estimation Marquette Uversty Multvarate Trasformato of Varables ad Maxmum Lkelhood Estmato Dael B. Rowe, Ph.D. Assocate Professor Departmet of Mathematcs, Statstcs, ad Computer Scece Copyrght 03 by Marquette Uversty

More information

To use adaptive cluster sampling we must first make some definitions of the sampling universe:

To use adaptive cluster sampling we must first make some definitions of the sampling universe: 8.3 ADAPTIVE SAMPLING Most of the methods dscussed samplg theory are lmted to samplg desgs hch the selecto of the samples ca be doe before the survey, so that oe of the decsos about samplg deped ay ay

More information

Strong Convergence of Weighted Averaged Approximants of Asymptotically Nonexpansive Mappings in Banach Spaces without Uniform Convexity

Strong Convergence of Weighted Averaged Approximants of Asymptotically Nonexpansive Mappings in Banach Spaces without Uniform Convexity BULLETIN of the MALAYSIAN MATHEMATICAL SCIENCES SOCIETY Bull. Malays. Math. Sc. Soc. () 7 (004), 5 35 Strog Covergece of Weghted Averaged Appromats of Asymptotcally Noepasve Mappgs Baach Spaces wthout

More information

On generalized fuzzy mean code word lengths. Department of Mathematics, Jaypee University of Engineering and Technology, Guna, Madhya Pradesh, India

On generalized fuzzy mean code word lengths. Department of Mathematics, Jaypee University of Engineering and Technology, Guna, Madhya Pradesh, India merca Joural of ppled Mathematcs 04; (4): 7-34 Publshed ole ugust 30, 04 (http://www.scecepublshggroup.com//aam) do: 0.648/.aam.04004.3 ISSN: 330-0043 (Prt); ISSN: 330-006X (Ole) O geeralzed fuzzy mea

More information

International Journal of Mathematical Archive-5(8), 2014, Available online through ISSN

International Journal of Mathematical Archive-5(8), 2014, Available online through   ISSN Iteratoal Joural of Mathematcal Archve-5(8) 204 25-29 Avalable ole through www.jma.fo ISSN 2229 5046 COMMON FIXED POINT OF GENERALIZED CONTRACTION MAPPING IN FUZZY METRIC SPACES Hamd Mottagh Golsha* ad

More information

Functions of Random Variables

Functions of Random Variables Fuctos of Radom Varables Chapter Fve Fuctos of Radom Varables 5. Itroducto A geeral egeerg aalyss model s show Fg. 5.. The model output (respose) cotas the performaces of a system or product, such as weght,

More information

A New Measure of Probabilistic Entropy. and its Properties

A New Measure of Probabilistic Entropy. and its Properties Appled Mathematcal Sceces, Vol. 4, 200, o. 28, 387-394 A New Measure of Probablstc Etropy ad ts Propertes Rajeesh Kumar Departmet of Mathematcs Kurukshetra Uversty Kurukshetra, Ida rajeesh_kuk@redffmal.com

More information

Lecture 3 Probability review (cont d)

Lecture 3 Probability review (cont d) STATS 00: Itroducto to Statstcal Iferece Autum 06 Lecture 3 Probablty revew (cot d) 3. Jot dstrbutos If radom varables X,..., X k are depedet, the ther dstrbuto may be specfed by specfyg the dvdual dstrbuto

More information

TRIANGULAR MEMBERSHIP FUNCTIONS FOR SOLVING SINGLE AND MULTIOBJECTIVE FUZZY LINEAR PROGRAMMING PROBLEM.

TRIANGULAR MEMBERSHIP FUNCTIONS FOR SOLVING SINGLE AND MULTIOBJECTIVE FUZZY LINEAR PROGRAMMING PROBLEM. Abbas Iraq Joural of SceceVol 53No 12012 Pp. 125-129 TRIANGULAR MEMBERSHIP FUNCTIONS FOR SOLVING SINGLE AND MULTIOBJECTIVE FUZZY LINEAR PROGRAMMING PROBLEM. Iraq Tarq Abbas Departemet of Mathematc College

More information

Module 7. Lecture 7: Statistical parameter estimation

Module 7. Lecture 7: Statistical parameter estimation Lecture 7: Statstcal parameter estmato Parameter Estmato Methods of Parameter Estmato 1) Method of Matchg Pots ) Method of Momets 3) Mamum Lkelhood method Populato Parameter Sample Parameter Ubased estmato

More information

A Conventional Approach for the Solution of the Fifth Order Boundary Value Problems Using Sixth Degree Spline Functions

A Conventional Approach for the Solution of the Fifth Order Boundary Value Problems Using Sixth Degree Spline Functions Appled Matheatcs, 1, 4, 8-88 http://d.do.org/1.4/a.1.448 Publshed Ole Aprl 1 (http://www.scrp.org/joural/a) A Covetoal Approach for the Soluto of the Ffth Order Boudary Value Probles Usg Sth Degree Sple

More information

Bayes Interval Estimation for binomial proportion and difference of two binomial proportions with Simulation Study

Bayes Interval Estimation for binomial proportion and difference of two binomial proportions with Simulation Study IJIEST Iteratoal Joural of Iovatve Scece, Egeerg & Techology, Vol. Issue 5, July 04. Bayes Iterval Estmato for bomal proporto ad dfferece of two bomal proportos wth Smulato Study Masoud Gaj, Solmaz hlmad

More information

Complete Convergence for Weighted Sums of Arrays of Rowwise Asymptotically Almost Negative Associated Random Variables

Complete Convergence for Weighted Sums of Arrays of Rowwise Asymptotically Almost Negative Associated Random Variables A^VÇÚO 1 32 ò 1 5 Ï 2016 c 10 Chese Joural of Appled Probablty ad Statstcs Oct., 2016, Vol. 32, No. 5, pp. 489-498 do: 10.3969/j.ss.1001-4268.2016.05.005 Complete Covergece for Weghted Sums of Arrays of

More information

Summary of the lecture in Biostatistics

Summary of the lecture in Biostatistics Summary of the lecture Bostatstcs Probablty Desty Fucto For a cotuos radom varable, a probablty desty fucto s a fucto such that: 0 dx a b) b a dx A probablty desty fucto provdes a smple descrpto of the

More information

Introduction to Matrices and Matrix Approach to Simple Linear Regression

Introduction to Matrices and Matrix Approach to Simple Linear Regression Itroducto to Matrces ad Matrx Approach to Smple Lear Regresso Matrces Defto: A matrx s a rectagular array of umbers or symbolc elemets I may applcatos, the rows of a matrx wll represet dvduals cases (people,

More information

Multi Objective Fuzzy Inventory Model with. Demand Dependent Unit Cost and Lead Time. Constraints A Karush Kuhn Tucker Conditions.

Multi Objective Fuzzy Inventory Model with. Demand Dependent Unit Cost and Lead Time. Constraints A Karush Kuhn Tucker Conditions. It. Joural of Math. Aalyss, Vol. 8, 204, o. 4, 87-93 HIKARI Ltd, www.m-hkar.com http://dx.do.org/0.2988/jma.204.30252 Mult Objectve Fuzzy Ivetory Model wth Demad Depedet Ut Cost ad Lead Tme Costrats A

More information

. The set of these sums. be a partition of [ ab, ]. Consider the sum f( x) f( x 1)

. The set of these sums. be a partition of [ ab, ]. Consider the sum f( x) f( x 1) Chapter 7 Fuctos o Bouded Varato. Subject: Real Aalyss Level: M.Sc. Source: Syed Gul Shah (Charma, Departmet o Mathematcs, US Sargodha Collected & Composed by: Atq ur Rehma (atq@mathcty.org, http://www.mathcty.org

More information

ON THE LOGARITHMIC INTEGRAL

ON THE LOGARITHMIC INTEGRAL Hacettepe Joural of Mathematcs ad Statstcs Volume 39(3) (21), 393 41 ON THE LOGARITHMIC INTEGRAL Bra Fsher ad Bljaa Jolevska-Tueska Receved 29:9 :29 : Accepted 2 :3 :21 Abstract The logarthmc tegral l(x)

More information

Unimodality Tests for Global Optimization of Single Variable Functions Using Statistical Methods

Unimodality Tests for Global Optimization of Single Variable Functions Using Statistical Methods Malaysa Umodalty Joural Tests of Mathematcal for Global Optmzato Sceces (): of 05 Sgle - 5 Varable (007) Fuctos Usg Statstcal Methods Umodalty Tests for Global Optmzato of Sgle Varable Fuctos Usg Statstcal

More information

2006 Jamie Trahan, Autar Kaw, Kevin Martin University of South Florida United States of America

2006 Jamie Trahan, Autar Kaw, Kevin Martin University of South Florida United States of America SOLUTION OF SYSTEMS OF SIMULTANEOUS LINEAR EQUATIONS Gauss-Sedel Method 006 Jame Traha, Autar Kaw, Kev Mart Uversty of South Florda Uted States of Amerca kaw@eg.usf.edu Itroducto Ths worksheet demostrates

More information

A NEW LOG-NORMAL DISTRIBUTION

A NEW LOG-NORMAL DISTRIBUTION Joural of Statstcs: Advaces Theory ad Applcatos Volume 6, Number, 06, Pages 93-04 Avalable at http://scetfcadvaces.co. DOI: http://dx.do.org/0.864/jsata_700705 A NEW LOG-NORMAL DISTRIBUTION Departmet of

More information

Estimation of Stress- Strength Reliability model using finite mixture of exponential distributions

Estimation of Stress- Strength Reliability model using finite mixture of exponential distributions Iteratoal Joural of Computatoal Egeerg Research Vol, 0 Issue, Estmato of Stress- Stregth Relablty model usg fte mxture of expoetal dstrbutos K.Sadhya, T.S.Umamaheswar Departmet of Mathematcs, Lal Bhadur

More information

The Mathematical Appendix

The Mathematical Appendix The Mathematcal Appedx Defto A: If ( Λ, Ω, where ( λ λ λ whch the probablty dstrbutos,,..., Defto A. uppose that ( Λ,,..., s a expermet type, the σ-algebra o λ λ λ are defed s deoted by ( (,,...,, σ Ω.

More information

Midterm Exam 1, section 1 (Solution) Thursday, February hour, 15 minutes

Midterm Exam 1, section 1 (Solution) Thursday, February hour, 15 minutes coometrcs, CON Sa Fracsco State Uversty Mchael Bar Sprg 5 Mdterm am, secto Soluto Thursday, February 6 hour, 5 mutes Name: Istructos. Ths s closed book, closed otes eam.. No calculators of ay kd are allowed..

More information

Special Instructions / Useful Data

Special Instructions / Useful Data JAM 6 Set of all real umbers P A..d. B, p Posso Specal Istructos / Useful Data x,, :,,, x x Probablty of a evet A Idepedetly ad detcally dstrbuted Bomal dstrbuto wth parameters ad p Posso dstrbuto wth

More information

COMPROMISE HYPERSPHERE FOR STOCHASTIC DOMINANCE MODEL

COMPROMISE HYPERSPHERE FOR STOCHASTIC DOMINANCE MODEL Sebasta Starz COMPROMISE HYPERSPHERE FOR STOCHASTIC DOMINANCE MODEL Abstract The am of the work s to preset a method of rakg a fte set of dscrete radom varables. The proposed method s based o two approaches:

More information

arxiv: v1 [math.st] 24 Oct 2016

arxiv: v1 [math.st] 24 Oct 2016 arxv:60.07554v [math.st] 24 Oct 206 Some Relatoshps ad Propertes of the Hypergeometrc Dstrbuto Peter H. Pesku, Departmet of Mathematcs ad Statstcs York Uversty, Toroto, Otaro M3J P3, Caada E-mal: pesku@pascal.math.yorku.ca

More information

Econometric Methods. Review of Estimation

Econometric Methods. Review of Estimation Ecoometrc Methods Revew of Estmato Estmatg the populato mea Radom samplg Pot ad terval estmators Lear estmators Ubased estmators Lear Ubased Estmators (LUEs) Effcecy (mmum varace) ad Best Lear Ubased Estmators

More information

NP!= P. By Liu Ran. Table of Contents. The P versus NP problem is a major unsolved problem in computer

NP!= P. By Liu Ran. Table of Contents. The P versus NP problem is a major unsolved problem in computer NP!= P By Lu Ra Table of Cotets. Itroduce 2. Prelmary theorem 3. Proof 4. Expla 5. Cocluso. Itroduce The P versus NP problem s a major usolved problem computer scece. Iformally, t asks whether a computer

More information

On L- Fuzzy Sets. T. Rama Rao, Ch. Prabhakara Rao, Dawit Solomon And Derso Abeje.

On L- Fuzzy Sets. T. Rama Rao, Ch. Prabhakara Rao, Dawit Solomon And Derso Abeje. Iteratoal Joural of Fuzzy Mathematcs ad Systems. ISSN 2248-9940 Volume 3, Number 5 (2013), pp. 375-379 Research Ida Publcatos http://www.rpublcato.com O L- Fuzzy Sets T. Rama Rao, Ch. Prabhakara Rao, Dawt

More information

PROJECTION PROBLEM FOR REGULAR POLYGONS

PROJECTION PROBLEM FOR REGULAR POLYGONS Joural of Mathematcal Sceces: Advaces ad Applcatos Volume, Number, 008, Pages 95-50 PROJECTION PROBLEM FOR REGULAR POLYGONS College of Scece Bejg Forestry Uversty Bejg 0008 P. R. Cha e-mal: sl@bjfu.edu.c

More information

C-1: Aerodynamics of Airfoils 1 C-2: Aerodynamics of Airfoils 2 C-3: Panel Methods C-4: Thin Airfoil Theory

C-1: Aerodynamics of Airfoils 1 C-2: Aerodynamics of Airfoils 2 C-3: Panel Methods C-4: Thin Airfoil Theory ROAD MAP... AE301 Aerodyamcs I UNIT C: 2-D Arfols C-1: Aerodyamcs of Arfols 1 C-2: Aerodyamcs of Arfols 2 C-3: Pael Methods C-4: Th Arfol Theory AE301 Aerodyamcs I Ut C-3: Lst of Subects Problem Solutos?

More information

1 Review and Overview

1 Review and Overview CS9T/STATS3: Statstcal Learg Teory Lecturer: Tegyu Ma Lecture #7 Scrbe: Bra Zag October 5, 08 Revew ad Overvew We wll frst gve a bref revew of wat as bee covered so far I te frst few lectures, we stated

More information

Lecture Note to Rice Chapter 8

Lecture Note to Rice Chapter 8 ECON 430 HG revsed Nov 06 Lecture Note to Rce Chapter 8 Radom matrces Let Y, =,,, m, =,,, be radom varables (r.v. s). The matrx Y Y Y Y Y Y Y Y Y Y = m m m s called a radom matrx ( wth a ot m-dmesoal dstrbuto,

More information

Journal of Mathematical Analysis and Applications

Journal of Mathematical Analysis and Applications J. Math. Aal. Appl. 365 200) 358 362 Cotets lsts avalable at SceceDrect Joural of Mathematcal Aalyss ad Applcatos www.elsever.com/locate/maa Asymptotc behavor of termedate pots the dfferetal mea value

More information

Square Difference Labeling Of Some Path, Fan and Gear Graphs

Square Difference Labeling Of Some Path, Fan and Gear Graphs Iteratoal Joural of Scetfc & Egeerg Research Volume 4, Issue3, March-03 ISSN 9-558 Square Dfferece Labelg Of Some Path, Fa ad Gear Graphs J.Shama Assstat Professor Departmet of Mathematcs CMS College of

More information

Class 13,14 June 17, 19, 2015

Class 13,14 June 17, 19, 2015 Class 3,4 Jue 7, 9, 05 Pla for Class3,4:. Samplg dstrbuto of sample mea. The Cetral Lmt Theorem (CLT). Cofdece terval for ukow mea.. Samplg Dstrbuto for Sample mea. Methods used are based o CLT ( Cetral

More information

Generating Multivariate Nonnormal Distribution Random Numbers Based on Copula Function

Generating Multivariate Nonnormal Distribution Random Numbers Based on Copula Function 7659, Eglad, UK Joural of Iformato ad Computg Scece Vol. 2, No. 3, 2007, pp. 9-96 Geeratg Multvarate Noormal Dstrbuto Radom Numbers Based o Copula Fucto Xaopg Hu +, Jam He ad Hogsheg Ly School of Ecoomcs

More information

Research Article A New Derivation and Recursive Algorithm Based on Wronskian Matrix for Vandermonde Inverse Matrix

Research Article A New Derivation and Recursive Algorithm Based on Wronskian Matrix for Vandermonde Inverse Matrix Mathematcal Problems Egeerg Volume 05 Artcle ID 94757 7 pages http://ddoorg/055/05/94757 Research Artcle A New Dervato ad Recursve Algorthm Based o Wroska Matr for Vadermode Iverse Matr Qu Zhou Xja Zhag

More information

GENERALIZED METHOD OF MOMENTS CHARACTERISTICS AND ITS APPLICATION ON PANELDATA

GENERALIZED METHOD OF MOMENTS CHARACTERISTICS AND ITS APPLICATION ON PANELDATA Sc.It.(Lahore),26(3),985-990,2014 ISSN 1013-5316; CODEN: SINTE 8 GENERALIZED METHOD OF MOMENTS CHARACTERISTICS AND ITS APPLICATION ON PANELDATA Beradhta H. S. Utam 1, Warsoo 1, Da Kurasar 1, Mustofa Usma

More information

hp calculators HP 30S Statistics Averages and Standard Deviations Average and Standard Deviation Practice Finding Averages and Standard Deviations

hp calculators HP 30S Statistics Averages and Standard Deviations Average and Standard Deviation Practice Finding Averages and Standard Deviations HP 30S Statstcs Averages ad Stadard Devatos Average ad Stadard Devato Practce Fdg Averages ad Stadard Devatos HP 30S Statstcs Averages ad Stadard Devatos Average ad stadard devato The HP 30S provdes several

More information

Uniform asymptotical stability of almost periodic solution of a discrete multispecies Lotka-Volterra competition system

Uniform asymptotical stability of almost periodic solution of a discrete multispecies Lotka-Volterra competition system Iteratoal Joural of Egeerg ad Advaced Research Techology (IJEART) ISSN: 2454-9290, Volume-2, Issue-1, Jauary 2016 Uform asymptotcal stablty of almost perodc soluto of a dscrete multspeces Lotka-Volterra

More information

Comparison of Parameters of Lognormal Distribution Based On the Classical and Posterior Estimates

Comparison of Parameters of Lognormal Distribution Based On the Classical and Posterior Estimates Joural of Moder Appled Statstcal Methods Volume Issue Artcle 8 --03 Comparso of Parameters of Logormal Dstrbuto Based O the Classcal ad Posteror Estmates Raja Sulta Uversty of Kashmr, Sragar, Ida, hamzasulta8@yahoo.com

More information

Application of Calibration Approach for Regression Coefficient Estimation under Two-stage Sampling Design

Application of Calibration Approach for Regression Coefficient Estimation under Two-stage Sampling Design Authors: Pradp Basak, Kaustav Adtya, Hukum Chadra ad U.C. Sud Applcato of Calbrato Approach for Regresso Coeffcet Estmato uder Two-stage Samplg Desg Pradp Basak, Kaustav Adtya, Hukum Chadra ad U.C. Sud

More information

The Generalized Inverted Generalized Exponential Distribution with an Application to a Censored Data

The Generalized Inverted Generalized Exponential Distribution with an Application to a Censored Data J. Stat. Appl. Pro. 4, No. 2, 223-230 2015 223 Joural of Statstcs Applcatos & Probablty A Iteratoal Joural http://dx.do.org/10.12785/jsap/040204 The Geeralzed Iverted Geeralzed Expoetal Dstrbuto wth a

More information

Generalized Convex Functions on Fractal Sets and Two Related Inequalities

Generalized Convex Functions on Fractal Sets and Two Related Inequalities Geeralzed Covex Fuctos o Fractal Sets ad Two Related Iequaltes Huxa Mo, X Su ad Dogya Yu 3,,3School of Scece, Bejg Uversty of Posts ad Telecommucatos, Bejg,00876, Cha, Correspodece should be addressed

More information

Third handout: On the Gini Index

Third handout: On the Gini Index Thrd hadout: O the dex Corrado, a tala statstca, proposed (, 9, 96) to measure absolute equalt va the mea dfferece whch s defed as ( / ) where refers to the total umber of dvduals socet. Assume that. The

More information

Several Theorems for the Trace of Self-conjugate Quaternion Matrix

Several Theorems for the Trace of Self-conjugate Quaternion Matrix Moder Aled Scece Setember, 008 Several Theorems for the Trace of Self-cojugate Quatero Matrx Qglog Hu Deartmet of Egeerg Techology Xchag College Xchag, Schua, 6503, Cha E-mal: shjecho@6com Lm Zou(Corresodg

More information

Beam Warming Second-Order Upwind Method

Beam Warming Second-Order Upwind Method Beam Warmg Secod-Order Upwd Method Petr Valeta Jauary 6, 015 Ths documet s a part of the assessmet work for the subject 1DRP Dfferetal Equatos o Computer lectured o FNSPE CTU Prague. Abstract Ths documet

More information

Midterm Exam 1, section 2 (Solution) Thursday, February hour, 15 minutes

Midterm Exam 1, section 2 (Solution) Thursday, February hour, 15 minutes coometrcs, CON Sa Fracsco State Uverst Mchael Bar Sprg 5 Mdterm xam, secto Soluto Thursda, Februar 6 hour, 5 mutes Name: Istructos. Ths s closed book, closed otes exam.. No calculators of a kd are allowed..

More information

Cubic Nonpolynomial Spline Approach to the Solution of a Second Order Two-Point Boundary Value Problem

Cubic Nonpolynomial Spline Approach to the Solution of a Second Order Two-Point Boundary Value Problem Joural of Amerca Scece ;6( Cubc Nopolyomal Sple Approach to the Soluto of a Secod Order Two-Pot Boudary Value Problem W.K. Zahra, F.A. Abd El-Salam, A.A. El-Sabbagh ad Z.A. ZAk * Departmet of Egeerg athematcs

More information

Derivation of 3-Point Block Method Formula for Solving First Order Stiff Ordinary Differential Equations

Derivation of 3-Point Block Method Formula for Solving First Order Stiff Ordinary Differential Equations Dervato of -Pot Block Method Formula for Solvg Frst Order Stff Ordary Dfferetal Equatos Kharul Hamd Kharul Auar, Kharl Iskadar Othma, Zara Bb Ibrahm Abstract Dervato of pot block method formula wth costat

More information

Point Estimation: definition of estimators

Point Estimation: definition of estimators Pot Estmato: defto of estmators Pot estmator: ay fucto W (X,..., X ) of a data sample. The exercse of pot estmato s to use partcular fuctos of the data order to estmate certa ukow populato parameters.

More information

Bayes Estimator for Exponential Distribution with Extension of Jeffery Prior Information

Bayes Estimator for Exponential Distribution with Extension of Jeffery Prior Information Malaysa Joural of Mathematcal Sceces (): 97- (9) Bayes Estmator for Expoetal Dstrbuto wth Exteso of Jeffery Pror Iformato Hadeel Salm Al-Kutub ad Noor Akma Ibrahm Isttute for Mathematcal Research, Uverst

More information

Ordinary Least Squares Regression. Simple Regression. Algebra and Assumptions.

Ordinary Least Squares Regression. Simple Regression. Algebra and Assumptions. Ordary Least Squares egresso. Smple egresso. Algebra ad Assumptos. I ths part of the course we are gog to study a techque for aalysg the lear relatoshp betwee two varables Y ad X. We have pars of observatos

More information

{ }{ ( )} (, ) = ( ) ( ) ( ) Chapter 14 Exercises in Sampling Theory. Exercise 1 (Simple random sampling): Solution:

{ }{ ( )} (, ) = ( ) ( ) ( ) Chapter 14 Exercises in Sampling Theory. Exercise 1 (Simple random sampling): Solution: Chapter 4 Exercses Samplg Theory Exercse (Smple radom samplg: Let there be two correlated radom varables X ad A sample of sze s draw from a populato by smple radom samplg wthout replacemet The observed

More information

Arithmetic Mean Suppose there is only a finite number N of items in the system of interest. Then the population arithmetic mean is

Arithmetic Mean Suppose there is only a finite number N of items in the system of interest. Then the population arithmetic mean is Topc : Probablty Theory Module : Descrptve Statstcs Measures of Locato Descrptve statstcs are measures of locato ad shape that perta to probablty dstrbutos The prmary measures of locato are the arthmetc

More information

Lecture 9: Tolerant Testing

Lecture 9: Tolerant Testing Lecture 9: Tolerat Testg Dael Kae Scrbe: Sakeerth Rao Aprl 4, 07 Abstract I ths lecture we prove a quas lear lower boud o the umber of samples eeded to do tolerat testg for L dstace. Tolerat Testg We have

More information

CHAPTER VI Statistical Analysis of Experimental Data

CHAPTER VI Statistical Analysis of Experimental Data Chapter VI Statstcal Aalyss of Expermetal Data CHAPTER VI Statstcal Aalyss of Expermetal Data Measuremets do ot lead to a uque value. Ths s a result of the multtude of errors (maly radom errors) that ca

More information

On Fuzzy Arithmetic, Possibility Theory and Theory of Evidence

On Fuzzy Arithmetic, Possibility Theory and Theory of Evidence O Fuzzy rthmetc, Possblty Theory ad Theory of Evdece suco P. Cucala, Jose Vllar Isttute of Research Techology Uversdad Potfca Comllas C/ Sata Cruz de Marceado 6 8 Madrd. Spa bstract Ths paper explores

More information

Chapter 14 Logistic Regression Models

Chapter 14 Logistic Regression Models Chapter 4 Logstc Regresso Models I the lear regresso model X β + ε, there are two types of varables explaatory varables X, X,, X k ad study varable y These varables ca be measured o a cotuous scale as

More information

22 Nonparametric Methods.

22 Nonparametric Methods. 22 oparametrc Methods. I parametrc models oe assumes apror that the dstrbutos have a specfc form wth oe or more ukow parameters ad oe tres to fd the best or atleast reasoably effcet procedures that aswer

More information

The Primitive Idempotents in

The Primitive Idempotents in Iteratoal Joural of Algebra, Vol, 00, o 5, 3 - The Prmtve Idempotets FC - I Kulvr gh Departmet of Mathematcs, H College r Jwa Nagar (rsa)-5075, Ida kulvrsheora@yahoocom K Arora Departmet of Mathematcs,

More information