Bayesian Estimation of the Logormal Distrbution Mean Using Ranked SET Sampling

Size: px
Start display at page:

Download "Bayesian Estimation of the Logormal Distrbution Mean Using Ranked SET Sampling"

Transcription

1 Basrah ournal o Sn Vol.5-7 Basan Estaton o th ooral Dstrbuton Man Usn Ran SET Sapln R.. h bstrat Bas staton or onoral an usn Ran St Sapln s onsr n ths papr an opar to that usn Spl Rano Sapln. It as sho that th Bas stator s bttr than Bas stator n trs o th Bas rs. lso th rato btn Bas rs to Bas rs s shon to b alas ratr than on. ريكان عبد العزيز احمد جامعة البصرة/ كلية الا دارة والاقتصاد/قسم الاحصاء الملخص لقد تم تقدير بييز للوسط الحسابي في حالة توزيع اللوغارتمي الطبيعي باستخدام طريقة المعاينة المرتبة ومقارنته بتقدير بييز بطريقة المعاينة العشواي ية البسيطة. وقد وجد ان تقدير بييز للمعاينة المرتبة ا فضل منه للمعاينة العشواي ية البسيطة من حيث الخطورة في تقدير بييز. وقد وجد ان النسبة بين خطورة تقدير بييز للمعاينة العشواي ية البسيطة الى خطورة بييز للمعاينة المرتبة داي ما اكبر من الواحد. Introuton Snha an Wu 994 nvstat th proran o n th staton o othr paratrs not ssntall th an hn th populaton s partall non. Th shap an th sal paratr o th to paratrs Wbull strbuton ar onsr n thr stu. Stos 995 µ onsr th loaton sal al th non stu σ ME ro both an or to ass snl paratr s unnon an both paratrs ar unnon. Bal Snha an Sutra 995 nvstat so provnts o µ th sutabl

2 Basrah ournal o Sn Vol.5-7 oatons o or staton o µ hn s noral an ponntal. In ths papr assu that th populaton unr stu s a onoral populaton th paratr an unnon an varan σ non an has a pror nst unton as. s an attpt to stat usn Basan staton a spl rano sapl o s s tan ro th populaton on th othr han a spl rano sapl o s s also tan ro th populaton to obtan th ran st sapl. or ah sapl th Basan stator s oun th rspt to th Conjuat an r prors. Th proran o th to stators ar opar usn thr Bas rss th to stators ar pn on th onjuat pror or opar usn thr rs unton th to stators ar pn on th r pror. n not that th squar rror loss unton SE ll b us n ths papr that ans a a rprsnt th loss that rsult ro stator b a. Th Bas stators th rspt to th Conjuat pror: Th onjuat prors hav th ntutvl appaln atur o allon on to bn th a rtan untonal or or th pror an n up th a postror o th sa untonal or but th upat paratrs b th sapl noraton as O.Brr. Th onjuat pror n ths as s noral strbuton an thout loss o nralt ll assu that t s ~ N. Th Bas stators pn on. N hr t b a ro lo σ σ non thn thout loss o nralt ta σ nst unton s. thn th probablt lo ~ > < <

3 R.. h Basan Estaton o 3 an th jont nst unton s. an th nst unton o th onjuat pror s Th postror nst unton o s thn Th Bas stator o s E baus th Bas stat th rspt to SE s th postror an thn lo an th Bas rs o th stator s Th Bas stators pn on. W assu that hav rano sapls ah o s sn. M M M lo < < lo lo ~ N Var E r

4 Basrah ournal o Sn Vol hr j N j lo ~. No lt Y Y Y b th hr n Y n n Y a Y.. Y s th th orr statst o th st. Thn th p o s vn b. hr Usn th transoraton lo thn ~ N.Thn p o s ba as. hr s a p o N an s a CD o N sn ar npnnt thr jont nst s. No t < < ;!!! < < > lo!!!!!!!!!

5 R.. h Basan Estaton o 5 & Thn Th postror nst unton o s vn b. Th Bas stator o s E n th postror varan s Th Bas rs Var E r Var

6 Basrah ournal o Sn Vol.5-7 Th nral Bas stators th rspt to th r pror: Th Basan approah an b us vn hn no pror noraton s avalabl n suh stuatons a non-noraton pror s us an b all r pror. Th Bas rs has no ann hr nnt so opar pn on th rs unton. Th nral Bas stators pn on. t b a ro lo N an lt th r pror n ths as s ~.Baus th s alloaton paratr s as O.Brr thn th postror nst s vn b. lo lo sn ~ N Hn th nral Bas stator o s. E Th rs unton s lo lo R bas Var Th nral Bas stators pn on. t Y Y Y b th ro lo N an lt th r pror n ths as s also ~. Usn th transoraton lo thn ~ N. Thn p o s ba as.!!! 6

7 R.. h Basan Estaton o 7 Thn th jont nst unton o 's s Thn th postror nst s vn b. thror Thus th nral Bas stator Th rs unton s vn b Proprts o th nral Bas stator usn. t b a onstant thn Proo: R

8 Basrah ournal o Sn Vol t thn Th rs unton o s r o. Proo: Usn proprt on. lt E R!!!!!!

9 R.. h Basan Estaton o 9 hh s r o. 3 proo: But. Thn t an j thn 4 s unbas stator or ; E Rss. proo: & j j Rss Rss E

10 Basrah ournal o Sn Vol.5-7 Usn proprt on an lt thn E!!! u an lt j usn th transoraton an usn th proprt thr hav. E u u u u j u u j rna u u rsptvl b thn E j j E Thus E E E E E E Thus s unbas stator or. Nural oparson. In ths ston ll usn th sulaton to obtan th valus o th Bas rs { r r } an rs unton { R R } pn on th onjuat pror an r pror rsptvl an also opar th to stators b usn n sn. Th n o th rspt to pn on th onjuat r pror s n b r Th n o th rspt to pn on th r pror s n b R R Tabl on ontans valus or & r r R R

11 R.. h Basan Estaton o alon th th n or slt valus o nubr o ls an s th st s. r & hr r s th Tabl :Bas rs { r r } an rs unton { R R } an n th rspt to th onjuat pror an r pror rsptvl Conluson.. Th Bas rs usn s alas lss than th Bas rs usn or all th ass onsr.

12 Basrah ournal o Sn Vol.5-7. Th rs unton usn th nral Bas stator s alas lss than that usn th nral Bas stator. 3. Both th Bas rs usn an rass as n r nrass. 4. Both th rss unton rass as r n nrass. 5. Th n s alas ratr than on. 6. Th n s nrasn thn a l as nrass. Rrns. Barr C. rnol & N. Balashnan rst Cours n Orr Statsts. ohn Wl & Sons. Bal K. Snha & Sutra On so aspts o ran st sapln or staton o noral an ponntal paratrs. Statsts an Dsons.. H. Snha B.K. an Wu's.994. Estaton o paratrs n to paratr Wbull an tr-valu strbutons usn ran st sapln. ournal o Statstal Rsarh as O. Brr 985. Statstal Dson Thor an Basan nalss. Son Eton. ohn Wl & Sons. Noran. ohnson 997.vans n th Thor an Prat o Statsts. ohn Wl & Sons Stos S Paratr ran st sapln. nnals o Insttut o Mathatal Statsts

ENGR 323 BHW 15 Van Bonn 1/7

ENGR 323 BHW 15 Van Bonn 1/7 ENGR 33 BHW 5 Van Bonn /7 4.4 In Eriss and 3 as wll as man othr situations on has th PDF o X and wishs th PDF o Yh. Assum that h is an invrtibl untion so that h an b solvd or to ild. Thn it an b shown

More information

A Probabilistic Characterization of Simulation Model Uncertainties

A Probabilistic Characterization of Simulation Model Uncertainties A Proalstc Charactrzaton of Sulaton Modl Uncrtants Vctor Ontvros Mohaad Modarrs Cntr for Rsk and Rlalty Unvrsty of Maryland 1 Introducton Thr s uncrtanty n odl prdctons as wll as uncrtanty n xprnts Th

More information

MA1506 Tutorial 2 Solutions. Question 1. (1a) 1 ) y x. e x. 1 exp (in general, Integrating factor is. ye dx. So ) (1b) e e. e c.

MA1506 Tutorial 2 Solutions. Question 1. (1a) 1 ) y x. e x. 1 exp (in general, Integrating factor is. ye dx. So ) (1b) e e. e c. MA56 utorial Solutions Qustion a Intgrating fator is ln p p in gnral, multipl b p So b ln p p sin his kin is all a Brnoulli quation -- st Sin w fin Y, Y Y, Y Y p Qustion Dfin v / hn our quation is v μ

More information

Priority Search Trees - Part I

Priority Search Trees - Part I .S. 252 Pro. Rorto Taassa oputatoal otry S., 1992 1993 Ltur 9 at: ar 8, 1993 Sr: a Q ol aro Prorty Sar Trs - Part 1 trouto t last ltur, w loo at trval trs. or trval pot losur prols, ty us lar spa a optal

More information

Solutions to Homework 5

Solutions to Homework 5 Solutions to Homwork 5 Pro. Silvia Frnánz Disrt Mathmatis Math 53A, Fall 2008. [3.4 #] (a) Thr ar x olor hois or vrtx an x or ah o th othr thr vrtis. So th hromati polynomial is P (G, x) =x (x ) 3. ()

More information

CS 491 G Combinatorial Optimization

CS 491 G Combinatorial Optimization CS 49 G Cobinatorial Optiization Lctur Nots Junhui Jia. Maiu Flow Probls Now lt us iscuss or tails on aiu low probls. Thor. A asibl low is aiu i an only i thr is no -augnting path. Proo: Lt P = A asibl

More information

Petru P. Blaga-Reducing of variance by a combined scheme based on Bernstein polynomials

Petru P. Blaga-Reducing of variance by a combined scheme based on Bernstein polynomials Ptru P Blaa-Rdu o vara by a obd sh basd o Brst olyoals REUCG OF VARACE BY A COMBE SCHEME BASE O BERSTE POYOMAS by Ptru P Blaa Abstrat A obd sh o th otrol varats ad whtd uor sal thods or rdu o vara s vstatd

More information

5/1/2018. Huffman Coding Trees. Huffman Coding Trees. Huffman Coding Trees. Huffman Coding Trees. Huffman Coding Trees. Huffman Coding Trees

5/1/2018. Huffman Coding Trees. Huffman Coding Trees. Huffman Coding Trees. Huffman Coding Trees. Huffman Coding Trees. Huffman Coding Trees /1/018 W usully no strns y ssnn -lnt os to ll rtrs n t lpt (or mpl, 8-t on n ASCII). Howvr, rnt rtrs our wt rnt rquns, w n sv mmory n ru trnsmttl tm y usn vrl-lnt non. T s to ssn sortr os to rtrs tt our

More information

Power Spectrum Estimation of Stochastic Stationary Signals

Power Spectrum Estimation of Stochastic Stationary Signals ag of 6 or Spctru stato of Stochastc Statoary Sgas Lt s cosr a obsrvato of a stochastc procss (). Ay obsrvato s a ft rcor of th ra procss. Thrfor, ca say:

More information

Calculus Revision A2 Level

Calculus Revision A2 Level alculus Rvision A Lvl Tabl of drivativs a n sin cos tan d an sc n cos sin Fro AS * NB sc cos sc cos hain rul othrwis known as th function of a function or coposit rul. d d Eapl (i) (ii) Obtain th drivativ

More information

Outline. 1 Introduction. 2 Min-Cost Spanning Trees. 4 Example

Outline. 1 Introduction. 2 Min-Cost Spanning Trees. 4 Example Outlin Computr Sin 33 Computtion o Minimum-Cost Spnnin Trs Prim's Alorithm Introution Mik Joson Dprtmnt o Computr Sin Univrsity o Clry Ltur #33 3 Alorithm Gnrl Constrution Mik Joson (Univrsity o Clry)

More information

Steinberg s Conjecture is false

Steinberg s Conjecture is false Stinrg s Conjtur is als arxiv:1604.05108v2 [math.co] 19 Apr 2016 Vinnt Cohn-Aa Mihal Hig Danil Král Zhntao Li Estan Salgao Astrat Stinrg onjtur in 1976 that vry planar graph with no yls o lngth our or

More information

Shortest Paths in Graphs. Paths in graphs. Shortest paths CS 445. Alon Efrat Slides courtesy of Erik Demaine and Carola Wenk

Shortest Paths in Graphs. Paths in graphs. Shortest paths CS 445. Alon Efrat Slides courtesy of Erik Demaine and Carola Wenk S 445 Shortst Paths n Graphs lon frat Sls courtsy of rk man an arola Wnk Paths n raphs onsr a raph G = (V, ) wth -wht functon w : R. Th wht of path p = v v v k s fn to xampl: k = w ( p) = w( v, v + ).

More information

Lecture 20: Minimum Spanning Trees (CLRS 23)

Lecture 20: Minimum Spanning Trees (CLRS 23) Ltur 0: Mnmum Spnnn Trs (CLRS 3) Jun, 00 Grps Lst tm w n (wt) rps (unrt/rt) n ntrou s rp voulry (vrtx,, r, pt, onnt omponnts,... ) W lso suss jny lst n jny mtrx rprsntton W wll us jny lst rprsntton unlss

More information

Potential Games and the Inefficiency of Equilibrium

Potential Games and the Inefficiency of Equilibrium Optmzaton and Control o Ntork Potntal Gam and th Inny o Equlbrum Ljun Chn 3/8/216 Outln Potntal gam q Rv on tratg gam q Potntal gam atom and nonatom Inny o qulbrum q Th pr o anarhy and lh routng q Rour

More information

Some Results on Interval Valued Fuzzy Neutrosophic Soft Sets ISSN

Some Results on Interval Valued Fuzzy Neutrosophic Soft Sets ISSN Som Rsults on ntrval Valud uzzy Nutrosophi Soft Sts SSN 239-9725. rokiarani Dpartmnt of Mathmatis Nirmala ollg for Womn oimbator amilnadu ndia. R. Sumathi Dpartmnt of Mathmatis Nirmala ollg for Womn oimbator

More information

( ) Differential Equations. Unit-7. Exact Differential Equations: M d x + N d y = 0. Verify the condition

( ) Differential Equations. Unit-7. Exact Differential Equations: M d x + N d y = 0. Verify the condition Diffrntial Equations Unit-7 Eat Diffrntial Equations: M d N d 0 Vrif th ondition M N Thn intgrat M d with rspt to as if wr onstants, thn intgrat th trms in N d whih do not ontain trms in and quat sum of

More information

VTU NOTES QUESTION PAPERS NEWS RESULTS FORUMS

VTU NOTES QUESTION PAPERS NEWS RESULTS FORUMS Diffrntial Equations Unit-7 Eat Diffrntial Equations: M d N d 0 Vrif th ondition M N Thn intgrat M d with rspt to as if wr onstants, thn intgrat th trms in N d whih do not ontain trms in and quat sum of

More information

Estimation of Population Variance Using a Generalized Double Sampling Estimator

Estimation of Population Variance Using a Generalized Double Sampling Estimator r Laka Joural o Appl tatstcs Vol 5-3 stmato o Populato Varac Us a Gralz Doubl ampl stmator Push Msra * a R. Kara h Dpartmt o tatstcs D.A.V.P.G. Coll Dhrau- 8 Uttarakha Ia. Dpartmt o tatstcs Luckow Uvrst

More information

Yong-Hwan Lee School of Electrical Engineering and INMC Seoul National University Kwanak P. O. Box 34, Seoul Korea

Yong-Hwan Lee School of Electrical Engineering and INMC Seoul National University Kwanak P. O. Box 34, Seoul Korea Har Dcson obnng-bas oopratv Spctru Snsng n ogntv Rao Systs Sung-Han School o Elctrcal Engnrng an INM Soul Natonal Unvrsty Kana P O Box 34 Soul 5-6 Kora lsh8@ttlsnuacr Dong-han Oh School o Elctrcal Engnrng

More information

Kernels. ffl A kernel K is a function of two objects, for example, two sentence/tree pairs (x1; y1) and (x2; y2)

Kernels. ffl A kernel K is a function of two objects, for example, two sentence/tree pairs (x1; y1) and (x2; y2) Krnls krnl K is a function of two ojcts, for xampl, two sntnc/tr pairs (x1; y1) an (x2; y2) K((x1; y1); (x2; y2)) Intuition: K((x1; y1); (x2; y2)) is a masur of th similarity (x1; y1) twn (x2; y2) an ormally:

More information

a b ixā + y b ixb + ay

a b ixā + y b ixb + ay Albrai Topoloy: Solution St #5 1) Lt G,, and x X. Baus X is Hausdor and x φ (x), thr ar opn nihborhoods U x o x and U φ(x) o φ (x) whih ar disjoint. Thn V,x : U x φ 1 (U φ(x)), is also an opn nihborhood

More information

Where k is either given or determined from the data and c is an arbitrary constant.

Where k is either given or determined from the data and c is an arbitrary constant. Exponntial growth and dcay applications W wish to solv an quation that has a drivativ. dy ky k > dx This quation says that th rat of chang of th function is proportional to th function. Th solution is

More information

Inference on Stress-Strength Reliability for Weighted Weibull Distribution

Inference on Stress-Strength Reliability for Weighted Weibull Distribution Arca Joural of Mathatcs a Statstcs 03, 3(4: 0-6 DOI: 0.593/j.ajs.030304.06 Ifrc o Strss-Strgth Rlablty for Wght Wbull Dstrbuto Hay M. Sal Dpartt of Statstcs, Faculty of Corc, Al-Azhr Uvrsty, Egypt & Qass

More information

Matched Quick Switching Variable Sampling System with Quick Switching Attribute Sampling System

Matched Quick Switching Variable Sampling System with Quick Switching Attribute Sampling System Natur and Sn 9;7( g v, t al, Samlng Systm Mathd Quk Swthng Varabl Samlng Systm wth Quk Swthng Attrbut Samlng Systm Srramahandran G.V, Palanvl.M Dartmnt of Mathmats, Dr.Mahalngam Collg of Engnrng and Thnology,

More information

Cycles and Simple Cycles. Paths and Simple Paths. Trees. Problem: There is No Completely Standard Terminology!

Cycles and Simple Cycles. Paths and Simple Paths. Trees. Problem: There is No Completely Standard Terminology! Outlin Computr Sin 331, Spnnin, n Surphs Mik Joson Dprtmnt o Computr Sin Univrsity o Clry Ltur #30 1 Introution 2 3 Dinition 4 Spnnin 5 6 Mik Joson (Univrsity o Clry) Computr Sin 331 Ltur #30 1 / 20 Mik

More information

Examples and applications on SSSP and MST

Examples and applications on SSSP and MST Exampls an applications on SSSP an MST Dan (Doris) H & Junhao Gan ITEE Univrsity of Qunslan COMP3506/7505, Uni of Qunslan Exampls an applications on SSSP an MST Dijkstra s Algorithm Th algorithm solvs

More information

Images Segmentation Based on Fast Otsu Method Implementing on Various Edge Detection Operators

Images Segmentation Based on Fast Otsu Method Implementing on Various Edge Detection Operators Images Segmentation Based on Fast Method Implementing on Various Edge Detection Operators Hameed M. Abdul jabar Amal J. Hatem Taghreed A. Naji Dept. of Physics, College of Education for Pure Science Ibn

More information

First derivative analysis

First derivative analysis Robrto s Nots on Dirntial Calculus Chaptr 8: Graphical analysis Sction First drivativ analysis What you nd to know alrady: How to us drivativs to idntiy th critical valus o a unction and its trm points

More information

Inner Product Spaces INNER PRODUCTS

Inner Product Spaces INNER PRODUCTS MA4Hcdoc Ir Product Spcs INNER PRODCS Dto A r product o vctor spc V s ucto tht ssgs ubr spc V such wy tht th ollowg xos holds: P : w s rl ubr P : P : P 4 : P 5 : v, w = w, v v + w, u = u + w, u rv, w =

More information

nd the particular orthogonal trajectory from the family of orthogonal trajectories passing through point (0; 1).

nd the particular orthogonal trajectory from the family of orthogonal trajectories passing through point (0; 1). Eamn EDO. Givn th family of curvs y + C nd th particular orthogonal trajctory from th family of orthogonal trajctoris passing through point (0; ). Solution: In th rst plac, lt us calculat th di rntial

More information

Spanning Trees. BFS, DFS spanning tree Minimum spanning tree. March 28, 2018 Cinda Heeren / Geoffrey Tien 1

Spanning Trees. BFS, DFS spanning tree Minimum spanning tree. March 28, 2018 Cinda Heeren / Geoffrey Tien 1 Spnnn Trs BFS, DFS spnnn tr Mnmum spnnn tr Mr 28, 2018 Cn Hrn / Gory Tn 1 Dpt-rst sr Vsts vrts lon snl pt s r s t n o, n tn ktrks to t rst junton n rsums own notr pt Mr 28, 2018 Cn Hrn / Gory Tn 2 Dpt-rst

More information

Investigate the efficiency of Proposed Techniques To Improve Area Calculation Using Simpson And Trapezoidal Rules

Investigate the efficiency of Proposed Techniques To Improve Area Calculation Using Simpson And Trapezoidal Rules Investigate the efficiency of Proposed Techniques To Improve Area Calculation Using Simpson And Raga KHALIL, Egypt Key words: Area calculation; Simpson s rule; Trapezoidal rule; Circular segment; Paraola.

More information

FREE VIBRATION ANALYSIS OF FUNCTIONALLY GRADED BEAMS

FREE VIBRATION ANALYSIS OF FUNCTIONALLY GRADED BEAMS Journal of Appl Mathatcs an Coputatonal Mchancs, (), 9- FREE VIBRATION ANAYSIS OF FNCTIONAY GRADED BEAMS Stansław Kukla, Jowta Rychlwska Insttut of Mathatcs, Czstochowa nvrsty of Tchnology Czstochowa,

More information

fiziks Institute for NET/JRF, GATE, IIT JAM, M.Sc. Entrance, JEST, TIFR and GRE in Physics

fiziks Institute for NET/JRF, GATE, IIT JAM, M.Sc. Entrance, JEST, TIFR and GRE in Physics Atoic and olcular Physics JEST Q. Th binding nrgy of th hydrogn ato (lctron bound to proton) is.6 V. Th binding nrgy of positroniu (lctron bound to positron) is (a).6 / V (b).6 / 8 V (c).6 8 V (d).6 V.6

More information

Multivariate Ratio Estimation With Known Population Proportion Of Two Auxiliary Characters For Finite Population

Multivariate Ratio Estimation With Known Population Proportion Of Two Auxiliary Characters For Finite Population Multvarate Rato Estmaton Wth Knon Populaton Proporton Of To Auxlar haracters For Fnte Populaton *Raesh Sngh, *Sachn Mal, **A. A. Adeara, ***Florentn Smarandache *Department of Statstcs, Banaras Hndu Unverst,Varanas-5,

More information

On Generalized Fractional Hankel Transform

On Generalized Fractional Hankel Transform Int. ournal o Math. nalss Vol. 6 no. 8 883-896 On Generaled Fratonal ankel Transorm R. D. Tawade Pro.Ram Meghe Insttute o Tehnolog & Researh Badnera Inda rajendratawade@redmal.om. S. Gudadhe Dept.o Mathemats

More information

Structure and Features

Structure and Features Thust l Roll ans Thust Roll ans Stutu an atus Thust ans onsst of a psly ma a an olls. Thy hav hh ty an hh loa apats an an b us n small spas. Thust l Roll ans nopoat nl olls, whl Thust Roll ans nopoat ylnal

More information

( ) ( ) Chapter 1 Exercise 1A. x 3. 1 a x. + d. 1 1 e. 2 a. x x 2. 2 a. + 3 x. 3 2x. x 1. 3 a. 4 a. Exercise 1C. x + x + 3. Exercise 1B.

( ) ( ) Chapter 1 Exercise 1A. x 3. 1 a x. + d. 1 1 e. 2 a. x x 2. 2 a. + 3 x. 3 2x. x 1. 3 a. 4 a. Exercise 1C. x + x + 3. Exercise 1B. answrs Chaptr Ers A a + + + + + + + + + + + + g a a a 6 h + + + + + + + + + + + + + + + + ( + ) + 6 + + + + + + 8 + 0 + Ers B a + + + + + + + + + g h j a a + + + + + + + + + + + + + + + + + + + + + + +

More information

COHORT MBA. Exponential function. MATH review (part2) by Lucian Mitroiu. The LOG and EXP functions. Properties: e e. lim.

COHORT MBA. Exponential function. MATH review (part2) by Lucian Mitroiu. The LOG and EXP functions. Properties: e e. lim. MTH rviw part b Lucian Mitroiu Th LOG and EXP functions Th ponntial function p : R, dfind as Proprtis: lim > lim p Eponntial function Y 8 6 - -8-6 - - X Th natural logarithm function ln in US- log: function

More information

Regression Estimator Using Double Ranked Set Sampling

Regression Estimator Using Double Ranked Set Sampling Scence and Technolog 7 (00 3-3 00 Sultan Qaboos Unvest Regesson Estmato Usng Double Ranked Set Samplng Han M. Samaw* and Eman M. Tawalbeh** *Depatment of Mathematcs and Statstcs College of Scence Sultan

More information

3) Use the average steady-state equation to determine the dose. Note that only 100 mg tablets of aminophylline are available here.

3) Use the average steady-state equation to determine the dose. Note that only 100 mg tablets of aminophylline are available here. PHA 5127 Dsigning A Dosing Rgimn Answrs provi by Jry Stark Mr. JM is to b start on aminophyllin or th tratmnt o asthma. H is a non-smokr an wighs 60 kg. Dsign an oral osing rgimn or this patint such that

More information

Calculus II (MAC )

Calculus II (MAC ) Calculus II (MAC232-2) Tst 2 (25/6/25) Nam (PRINT): Plas show your work. An answr with no work rcivs no crdit. You may us th back of a pag if you nd mor spac for a problm. You may not us any calculators.

More information

Digital Signal Processing, Fall 2006

Digital Signal Processing, Fall 2006 Digital Signal Prossing, Fall 006 Ltur 7: Filtr Dsign Zhng-ua an Dpartmnt of Eltroni Systms Aalborg Univrsity, Dnmar t@om.aau. Cours at a glan MM Disrt-tim signals an systms Systm MM Fourir-omain rprsntation

More information

MATHEMATICS PAPER IB COORDINATE GEOMETRY(2D &3D) AND CALCULUS. Note: This question paper consists of three sections A,B and C.

MATHEMATICS PAPER IB COORDINATE GEOMETRY(2D &3D) AND CALCULUS. Note: This question paper consists of three sections A,B and C. MATHEMATICS PAPER IB COORDINATE GEOMETRY(D &D) AND CALCULUS. TIME : hrs Ma. Marks.75 Not: This qustion papr consists of thr sctions A,B and C. SECTION A VERY SHORT ANSWER TYPE QUESTIONS. 0X =0.If th portion

More information

1 Input-Output Stability

1 Input-Output Stability Inut-Outut Stability Inut-outut stability analysis allows us to analyz th stability of a givn syst without knowing th intrnal stat x of th syst. Bfor going forward, w hav to introduc so inut-outut athatical

More information

Solutions to Supplementary Problems

Solutions to Supplementary Problems Solution to Supplmntary Problm Chaptr 5 Solution 5. Failur of th tiff clay occur, hn th ffctiv prur at th bottom of th layr bcom ro. Initially Total ovrburn prur at X : = 9 5 + = 7 kn/m Por atr prur at

More information

Heisenberg Model. Sayed Mohammad Mahdi Sadrnezhaad. Supervisor: Prof. Abdollah Langari

Heisenberg Model. Sayed Mohammad Mahdi Sadrnezhaad. Supervisor: Prof. Abdollah Langari snbrg Modl Sad Mohammad Mahd Sadrnhaad Survsor: Prof. bdollah Langar bstract: n ths rsarch w tr to calculat analtcall gnvalus and gnvctors of fnt chan wth ½-sn artcls snbrg modl. W drov gnfuctons for closd

More information

Theorem 1. An undirected graph is a tree if and only if there is a unique simple path between any two of its vertices.

Theorem 1. An undirected graph is a tree if and only if there is a unique simple path between any two of its vertices. Cptr 11: Trs 11.1 - Introuton to Trs Dnton 1 (Tr). A tr s onnt unrt rp wt no sp ruts. Tor 1. An unrt rp s tr n ony tr s unqu sp pt twn ny two o ts vrts. Dnton 2. A root tr s tr n w on vrtx s n snt s t

More information

ANALYSIS IN THE FREQUENCY DOMAIN

ANALYSIS IN THE FREQUENCY DOMAIN ANALYSIS IN THE FREQUENCY DOMAIN SPECTRAL DENSITY Dfinition Th spctral dnsit of a S.S.P. t also calld th spctrum of t is dfind as: + { γ }. jτ γ τ F τ τ In othr words, of th covarianc function. is dfind

More information

Advanced Queueing Theory. M/G/1 Queueing Systems

Advanced Queueing Theory. M/G/1 Queueing Systems Advand Quung Thory Ths slds ar rad by Dr. Yh Huang of Gorg Mason Unvrsy. Sudns rgsrd n Dr. Huang's ourss a GMU an ma a sngl mahn-radabl opy and prn a sngl opy of ah sld for hr own rfrn, so long as ah sld

More information

Constructive Geometric Constraint Solving

Constructive Geometric Constraint Solving Construtiv Gomtri Constrint Solving Antoni Soto i Rir Dprtmnt Llngutgs i Sistms Inormàtis Univrsitt Politèni Ctluny Brlon, Sptmr 2002 CGCS p.1/37 Prliminris CGCS p.2/37 Gomtri onstrint prolm C 2 D L BC

More information

SUMMER 17 EXAMINATION

SUMMER 17 EXAMINATION (ISO/IEC - 7-5 Crtifid) SUMMER 7 EXAMINATION Modl wr jct Cod: Important Instructions to aminrs: ) Th answrs should b amind by ky words and not as word-to-word as givn in th modl answr schm. ) Th modl answr

More information

u x v x dx u x v x v x u x dx d u x v x u x v x dx u x v x dx Integration by Parts Formula

u x v x dx u x v x v x u x dx d u x v x u x v x dx u x v x dx Integration by Parts Formula 7. Intgration by Parts Each drivativ formula givs ris to a corrsponding intgral formula, as w v sn many tims. Th drivativ product rul yilds a vry usful intgration tchniqu calld intgration by parts. Starting

More information

ME 501A Seminar in Engineering Analysis Page 1

ME 501A Seminar in Engineering Analysis Page 1 St Ssts o Ordar Drtal Equatos Novbr 7 St Ssts o Ordar Drtal Equatos Larr Cartto Mcacal Er 5A Sar Er Aalss Novbr 7 Outl Mr Rsults Rvw last class Stablt o urcal solutos Stp sz varato or rror cotrol Multstp

More information

2. Finite Impulse Response Filters (FIR)

2. Finite Impulse Response Filters (FIR) .. Mthos for FIR filtrs implmntation. Finit Impuls Rspons Filtrs (FIR. Th winow mtho.. Frquncy charactristic uniform sampling. 3. Maximum rror minimizing. 4. Last-squars rror minimizing.. Mthos for FIR

More information

, each of which is a tree, and whose roots r 1. , respectively, are children of r. Data Structures & File Management

, each of which is a tree, and whose roots r 1. , respectively, are children of r. Data Structures & File Management nrl tr T is init st o on or mor nos suh tht thr is on sint no r, ll th root o T, n th rminin nos r prtition into n isjoint susts T, T,, T n, h o whih is tr, n whos roots r, r,, r n, rsptivly, r hilrn o

More information

Extension Formulas of Lauricella s Functions by Applications of Dixon s Summation Theorem

Extension Formulas of Lauricella s Functions by Applications of Dixon s Summation Theorem Avll t http:pvu.u Appl. Appl. Mth. ISSN: 9-9466 Vol. 0 Issu Dr 05 pp. 007-08 Appltos Appl Mthts: A Itrtol Jourl AAM Etso oruls of Lurll s utos Appltos of Do s Suto Thor Ah Al Atsh Dprtt of Mthts A Uvrst

More information

Numerical methods, Mixed exercise 10

Numerical methods, Mixed exercise 10 Numrial mthos, Mi ris a f ( ) 6 f ( ) 6 6 6 a = 6, b = f ( ) So. 6 b n a n 6 7.67... 6.99....67... 6.68....99... 6.667....68... To.p., th valus ar =.68, =.99, =.68, =.67. f (.6).6 6.6... f (.6).6 6.6.7...

More information

Introduction to Fourier optics. Textbook: Goodman (chapters 2-4) Overview:

Introduction to Fourier optics. Textbook: Goodman (chapters 2-4) Overview: Introuton to ourr opts Ttbook: Goon (ptrs -) Ovrv: nr n nvrnt ssts T ourr trnsor Slr rton rsnl n runor pprotons. . nr ssts n ourr trnsor tutorl (rnr) sst onnts n nput to n output su tt: It s s to b lnr

More information

Review - Probabilistic Classification

Review - Probabilistic Classification Mmoral Unvrsty of wfoundland Pattrn Rcognton Lctur 8 May 5, 6 http://www.ngr.mun.ca/~charlsr Offc Hours: Tusdays Thursdays 8:3-9:3 PM E- (untl furthr notc) Gvn lablld sampls { ɛc,,,..., } {. Estmat Rvw

More information

Analytical Study of near Mobility Edge Density of States of Hydrogenated Amorphous Silicon

Analytical Study of near Mobility Edge Density of States of Hydrogenated Amorphous Silicon Analytical Study of near Mobility Edge Density of States of Hydrogenated Amorphous Silicon Abdullah Ibrahim Abbo* Received 7, April, 2013 Accepted 12, November, 2013 Abstract: Experimental results for

More information

SAMPLE CSc 340 EXAM QUESTIONS WITH SOLUTIONS: part 2

SAMPLE CSc 340 EXAM QUESTIONS WITH SOLUTIONS: part 2 AMPLE C EXAM UETION WITH OLUTION: prt. It n sown tt l / wr.7888l. I Φ nots orul or pprotng t vlu o tn t n sown tt t trunton rror o ts pproton s o t or or so onstnts ; tt s Not tt / L Φ L.. Φ.. /. /.. Φ..787.

More information

Graphs. Graphs. Graphs: Basic Terminology. Directed Graphs. Dr Papalaskari 1

Graphs. Graphs. Graphs: Basic Terminology. Directed Graphs. Dr Papalaskari 1 CSC 00 Disrt Struturs : Introuon to Grph Thory Grphs Grphs CSC 00 Disrt Struturs Villnov Univrsity Grphs r isrt struturs onsisng o vrs n gs tht onnt ths vrs. Grphs n us to mol: omputr systms/ntworks mthml

More information

The University of Sydney MATH 2009

The University of Sydney MATH 2009 T Unvrsty o Syny MATH 2009 APH THEOY Tutorl 7 Solutons 2004 1. Lt t sonnt plnr rp sown. Drw ts ul, n t ul o t ul ( ). Sow tt s sonnt plnr rp, tn s onnt. Du tt ( ) s not somorp to. ( ) A onnt rp s on n

More information

The Elastic Scattering of Electrons from Cadmium Atom with the use of Model-Potential Approach

The Elastic Scattering of Electrons from Cadmium Atom with the use of Model-Potential Approach Basah Jounal of Scienec (A) Vol.6(),77-84, 008 The Elastic Scatteing of Electons fom Cadmium Atom with the use of Model-Potential Appoach A. A. Khalf Physics Depatment, College of Science, Univesity of

More information

A general N-dimensional vector consists of N values. They can be arranged as a column or a row and can be real or complex.

A general N-dimensional vector consists of N values. They can be arranged as a column or a row and can be real or complex. Lnr lgr Vctors gnrl -dmnsonl ctor conssts of lus h cn rrngd s column or row nd cn rl or compl Rcll -dmnsonl ctor cn rprsnt poston, loct, or cclrton Lt & k,, unt ctors long,, & rspctl nd lt k h th componnts

More information

A L A BA M A L A W R E V IE W

A L A BA M A L A W R E V IE W A L A BA M A L A W R E V IE W Volume 52 Fall 2000 Number 1 B E F O R E D I S A B I L I T Y C I V I L R I G HT S : C I V I L W A R P E N S I O N S A N D TH E P O L I T I C S O F D I S A B I L I T Y I N

More information

Hardy-Littlewood Conjecture and Exceptional real Zero. JinHua Fei. ChangLing Company of Electronic Technology Baoji Shannxi P.R.

Hardy-Littlewood Conjecture and Exceptional real Zero. JinHua Fei. ChangLing Company of Electronic Technology Baoji Shannxi P.R. Hardy-Littlwood Conjctur and Excptional ral Zro JinHua Fi ChangLing Company of Elctronic Tchnology Baoji Shannxi P.R.China E-mail: fijinhuayoujian@msn.com Abstract. In this papr, w assum that Hardy-Littlwood

More information

Integrated Optical Waveguides

Integrated Optical Waveguides Su Opls Faha Raa Cll Uvs Chap 8 Ia Opal Wavus 7 Dl Slab Wavus 7 Iu: A va f ff a pal wavus a us f a u lh a hp Th s bas pal wavu s a slab wavus shw blw Th suu s uf h - Lh s u s h b al al fl a h -la fas Cla

More information

Sixth and Fourth Order Compact Finite Difference Schemes for Two and Three Dimension Poisson Equation with Two Methods to derive These Schemes

Sixth and Fourth Order Compact Finite Difference Schemes for Two and Three Dimension Poisson Equation with Two Methods to derive These Schemes Basra Journal of Scienec (A) Vol.(),-0, 00 Sit and Fourt Order Compact Finite Difference Scemes for Two and Tree Dimension Poisson Equation wit Two Metods to derive Tese Scemes Akil J. Harfas Huda A. Jalob

More information

LR(0) Analysis. LR(0) Analysis

LR(0) Analysis. LR(0) Analysis LR() Analysis LR() Conlicts: Introuction Whn constructing th LR() analysis tal scri in th prvious stps, it has not n possil to gt a trministic analysr, caus thr ar svral possil actions in th sam cll. I

More information

(Minimum) Spanning Trees

(Minimum) Spanning Trees (Mnmum) Spnnn Trs Spnnn trs Kruskl's lortm Novmr 23, 2017 Cn Hrn / Gory Tn 1 Spnnn trs Gvn G = V, E, spnnn tr o G s onnt surp o G wt xtly V 1 s mnml sust o s tt onnts ll t vrts o G G = Spnnn trs Novmr

More information

Abstract Interpretation: concrete and abstract semantics

Abstract Interpretation: concrete and abstract semantics Abstract Intrprtation: concrt and abstract smantics Concrt smantics W considr a vry tiny languag that manags arithmtic oprations on intgrs valus. Th (concrt) smantics of th languags cab b dfind by th funzcion

More information

Propositional Logic. Combinatorial Problem Solving (CPS) Albert Oliveras Enric Rodríguez-Carbonell. May 17, 2018

Propositional Logic. Combinatorial Problem Solving (CPS) Albert Oliveras Enric Rodríguez-Carbonell. May 17, 2018 Propositional Logic Combinatorial Problm Solving (CPS) Albrt Olivras Enric Rodríguz-Carbonll May 17, 2018 Ovrviw of th sssion Dfinition of Propositional Logic Gnral Concpts in Logic Rduction to SAT CNFs

More information

EFFECT OF BOUNCING AND PITCHING ON THE COUPLED NATURAL FREQUENCY OF AN AUTOMOBILE

EFFECT OF BOUNCING AND PITCHING ON THE COUPLED NATURAL FREQUENCY OF AN AUTOMOBILE The Iraqi Journal For Mechanical And Material Engineering, Vol.11, No.3, 2011 EFFECT OF BOUNCING AND PITCHING ON THE COUPLED NATURAL FREQUENCY OF AN AUTOMOBILE Bushra Rasheed Mohameed Institute of Technology

More information

Nikon i-line Glass Series

Nikon i-line Glass Series Nkon ln la S ln la VNTS Nkon a an vlopmn of qualy maal a alway bn la o n fo ompany opal pou. Pon ky fao. van n la noloy pn upon pon, an a Nkon xl. Nkon ln la wa vlop fo u w ln ( nm) loapy un. I lv anman

More information

September 27, Introduction to Ordinary Differential Equations. ME 501A Seminar in Engineering Analysis Page 1. Outline

September 27, Introduction to Ordinary Differential Equations. ME 501A Seminar in Engineering Analysis Page 1. Outline Introucton to Ornar Dffrntal Equatons Sptmbr 7, 7 Introucton to Ornar Dffrntal Equatons Larr artto Mchancal Engnrng AB Smnar n Engnrng Analss Sptmbr 7, 7 Outln Rvw numrcal solutons Bascs of ffrntal quatons

More information

UNIT 8 TWO-WAY ANOVA WITH m OBSERVATIONS PER CELL

UNIT 8 TWO-WAY ANOVA WITH m OBSERVATIONS PER CELL UNIT 8 TWO-WAY ANOVA WITH OBSERVATIONS PER CELL Two-Way Anova wth Obsrvatons Pr Cll Structur 81 Introducton Obctvs 8 ANOVA Modl for Two-way Classfd Data wth Obsrvatons r Cll 83 Basc Assutons 84 Estaton

More information

Gradebook & Midterm & Office Hours

Gradebook & Midterm & Office Hours Your commnts So what do w do whn on of th r's is 0 in th quation GmM(1/r-1/r)? Do w nd to driv all of ths potntial nrgy formulas? I don't undrstand springs This was th first lctur I actually larnd somthing

More information

Assignment 4 Biophys 4322/5322

Assignment 4 Biophys 4322/5322 Assignmnt 4 Biophys 4322/5322 Tylr Shndruk Fbruary 28, 202 Problm Phillips 7.3. Part a R-onsidr dimoglobin utilizing th anonial nsmbl maning rdriv Eq. 3 from Phillips Chaptr 7. For a anonial nsmbl p E

More information

Journal of Babylon University/Engineering Sciences/ No.(4)/ Vol.(24): 2016

Journal of Babylon University/Engineering Sciences/ No.(4)/ Vol.(24): 2016 Balancing Axial Thrust in the Single Suction one stage Centrifugal Pump by Hydraulic Balance Holes. Abdulkareem Abdulwahab Ibrahim Babylon University / Engineering College / Mechanical Department abdulkareemwahab78@yahoo.com

More information

10. EXTENDING TRACTABILITY

10. EXTENDING TRACTABILITY Coping with NP-compltnss 0. EXTENDING TRACTABILITY ining small vrtx covrs solving NP-har problms on trs circular arc covrings vrtx covr in bipartit graphs Q. Suppos I n to solv an NP-complt problm. What

More information

TP A.31 The physics of squirt

TP A.31 The physics of squirt thnial proof TP A. Th physis of squirt supporting: Th Illustratd Prinipls of Pool and Billiards http://illiards.olostat.du y David G. Aliator, PhD, PE ("Dr. Dav") thnial proof originally postd: 8//7 last

More information

Vertical Sound Waves

Vertical Sound Waves Vral Sond Wavs On an drv h formla for hs avs by onsdrn drly h vral omonn of momnm qaon hrmodynam qaon and h onny qaon from 5 and hn follon h rrbaon mhod and assmn h snsodal solons. Effvly h frs ro and

More information

Building A 3D Geological model Using Petrel Software for Asmari Reservoir, South Eastern Iraq

Building A 3D Geological model Using Petrel Software for Asmari Reservoir, South Eastern Iraq Building A 3D Geological model Using Petrel Software for Asmari Reservoir, South Eastern Iraq Buraq.A. Al-Baldawi* Department of Geology, College of Science, Baghdad University. Baghdad, Iraq. Abstract

More information

0 t b r 6, 20 t l nf r nt f th l t th t v t f th th lv, ntr t n t th l l l nd d p rt nt th t f ttr t n th p nt t th r f l nd d tr b t n. R v n n th r

0 t b r 6, 20 t l nf r nt f th l t th t v t f th th lv, ntr t n t th l l l nd d p rt nt th t f ttr t n th p nt t th r f l nd d tr b t n. R v n n th r n r t d n 20 22 0: T P bl D n, l d t z d http:.h th tr t. r pd l 0 t b r 6, 20 t l nf r nt f th l t th t v t f th th lv, ntr t n t th l l l nd d p rt nt th t f ttr t n th p nt t th r f l nd d tr b t n.

More information

Bayesian Analysis of the Rao-Kupper Model for Paired Comparison with Order Effect

Bayesian Analysis of the Rao-Kupper Model for Paired Comparison with Order Effect ISSN 684-8403 Journal of Statsts Volue, 05. pp. 4-57 Abstrat Bayesan Analyss of the Rao-Kupper Model for Pared Coparson wth Order Effet Saa Altaf, Muhaad Asla and Muhaad Asla 3 Beause of the wde applablty

More information

Spectrophotometric Determination of Chlorocresol via Nitrosation Reaction Application to Pharmaceutical Preparations (Creams)*

Spectrophotometric Determination of Chlorocresol via Nitrosation Reaction Application to Pharmaceutical Preparations (Creams)* ------Jou. Raf. Sci., Vol. 20, No.3 pp 66-73, 2009 ------ Spectrophotometric Determination of Chlorocresol via Nitrosation Reaction Application to Pharmaceutical Preparations (Creams)* Nief R. Ahmed Widad

More information

Superposition. Thinning

Superposition. Thinning Suprposition STAT253/317 Wintr 213 Lctur 11 Yibi Huang Fbruary 1, 213 5.3 Th Poisson Procsss 5.4 Gnralizations of th Poisson Procsss Th sum of two indpndnt Poisson procsss with rspctiv rats λ 1 and λ 2,

More information

FOR MORE PAPERS LOGON TO

FOR MORE PAPERS LOGON TO IT430 - E-Commerce Quesion No: 1 ( Marks: 1 )- Please choose one MAC sand for M d a A ss Conro a M d a A ss Consor M r of As an Co n on of s Quesion No: 2 ( Marks: 1 )- Please choose one C oos orr HTML

More information

9 Kinetic Theory of Gases

9 Kinetic Theory of Gases Contnt 9 Kintic hory of Gass By Liw Sau oh 9. Ial gas quation 9. rssur of a gas 9. Molcular kintic nrgy 9.4 h r..s. sp of olculs 9.5 Dgrs of fro an law of quipartition of nrgy 9.6 Intrnal nrgy of an ial

More information

Junction Tree Algorithm 1. David Barber

Junction Tree Algorithm 1. David Barber Juntion Tr Algorithm 1 David Barbr Univrsity Collg London 1 Ths slids aompany th book Baysian Rasoning and Mahin Larning. Th book and dmos an b downloadd from www.s.ul.a.uk/staff/d.barbr/brml. Fdbak and

More information

(heat loss divided by total enthalpy flux) is of the order of 8-16 times

(heat loss divided by total enthalpy flux) is of the order of 8-16 times 16.51, Rok Prolson Prof. Manl Marnz-Sanhz r 8: Convv Ha ransfr: Ohr Effs Ovrall Ha oss and Prforman Effs of Ha oss (1) Ovrall Ha oss h loal ha loss r n ara s q = ρ ( ) ngrad ha loss s a S, and sng m =

More information

NEW APPLICATIONS OF THE ABEL-LIOUVILLE FORMULA

NEW APPLICATIONS OF THE ABEL-LIOUVILLE FORMULA NE APPLICATIONS OF THE ABEL-LIOUVILLE FORMULA Mirca I CÎRNU Ph Dp o Mathmatics III Faculty o Applid Scincs Univrsity Polithnica o Bucharst Cirnumirca @yahoocom Abstract In a rcnt papr [] 5 th indinit intgrals

More information

MATHEMATICS PAPER IIB COORDINATE GEOMETRY AND CALCULUS. Note: This question paper consists of three sections A, B and C.

MATHEMATICS PAPER IIB COORDINATE GEOMETRY AND CALCULUS. Note: This question paper consists of three sections A, B and C. MATHEMATICS PAPER IIB COORDINATE GEOMETRY AND CALCULUS. Tim: 3hrs Ma. Marks.75 Not: This qustion papr consists of thr sctions A, B and C. SECTION -A Vry Short Answr Typ Qustions. 0 X = 0. Find th condition

More information

Maxwellian Collisions

Maxwellian Collisions Maxwllian Collisions Maxwll ralizd arly on that th particular typ of collision in which th cross-sction varis at Q rs 1/g offrs drastic siplifications. Intrstingly, this bhavior is physically corrct for

More information

tcvrn Hl1 J M Hamilton P Eng Chief Geologist Kimberley Northing m Northing m I FEB 24 1QP Northing m Gold Commiuioner

tcvrn Hl1 J M Hamilton P Eng Chief Geologist Kimberley Northing m Northing m I FEB 24 1QP Northing m Gold Commiuioner SVA M OMO TD KOOT GROP ASSSSMT RPORT KMBRY B Th fwn rpr dsrbs h rss f drn Dand Dr H K 8 4 a 8 r h D D H K 8 5 a 9 5 r h D D H K 8 5A a 67 38 r h D D H K 8 6 a 8 69 r h and D D H K 8 7 a 77 72 r h n h ana

More information

COMP 250. Lecture 29. graph traversal. Nov. 15/16, 2017

COMP 250. Lecture 29. graph traversal. Nov. 15/16, 2017 COMP 250 Ltur 29 rp trvrsl Nov. 15/16, 2017 1 Toy Rursv rp trvrsl pt rst Non-rursv rp trvrsl pt rst rt rst 2 Hs up! Tr wr w mstks n t sls or S. 001 or toy s ltur. So you r ollown t ltur rorns n usn ts

More information

Estimation of the Population Mean Based on Extremes Ranked Set Sampling

Estimation of the Population Mean Based on Extremes Ranked Set Sampling Aerican Journal of Matheatics Statistics 05, 5(: 3-3 DOI: 0.593/j.ajs.05050.05 Estiation of the Population Mean Based on Extrees Ranked Set Sapling B. S. Biradar,*, Santosha C. D. Departent of Studies

More information