Application of Generating Functions to the Theory of Success Runs

Size: px
Start display at page:

Download "Application of Generating Functions to the Theory of Success Runs"

Transcription

1 Aled Mathematcal Sceces, Vol. 10, 2016, o. 50, HIKARI Ltd, htt://dx.do.org/ /ams Alcato of Geeratg Fuctos to the Theory of Success Rus B.M. Bekker, O.A. Ivaov ad V.V. Ivaova St. Petersburg State Uversty, Uverstetskaya ab., 7-9, St. Petersburg, Russa Coyrght c 2016 B.M. Bekker, O.A. Ivaov, ad V.V. Ivaova. Ths artcle s dstrbuted uder the Creatve Commos Attrbuto Lcese, whch ermts urestrcted use, dstrbuto, ad reroducto ay medum, rovded the orgal work s roerly cted. Abstract I the reset aer, we geeralze the results of the aers [2] ad [4] ad gve a ew roof of the exlct formula for the geeratg fucto of the umbers of trals before gettg k cosecutve successes. Mathematcs Subject Classfcato: 12J10 Keywords: Geeratg fucto, Beroull scheme 1 Itroducto We cosder the followg well-kow roblem: what s the exected umber of co tosses before two cosecutve heads are obtaed? A smlar questo ca be asked about a far sx-sded de: how may tmes do you have to roll before gettg a gve umber k of cosecutve sxes? Formally, the roblem ca be stated as follows. We cosder the Beroull scheme of trals whch success S occurs wth robablty ad falure F occurs wth robablty q = 1. Let X be the radom varable whose values are the umbers of trals before gettg a success ru of legth k. The geeratg fucto G X of X s well kow (see e.g., [3, Ch. XIII, Sec.7]. Noetheless, ths roblem stll attracts atteto of mathematcas. I the aers [2] ad [4], t s show that, the case = 1/2, the geeratg fucto G X s coected wth the geeratg fucto of the so-called k-fboacc umbers. Sce the geeratg fucto for these umbers s costructed a stadard way, oe has a ew roof of

2 2492 B.M. Bekker, O.A. Ivaov, ad V.V. Ivaova the formula for the geeratg fucto questo. I the reset aer, we geeralze these results to the case of a arbtrary. 2 Geeratg fucto of the umber of trals We cosder the sequeces of trals wth o success rus of legth k. Each such sequece ca be rereseted as a sequece of F s ad S s wth o k successve S s. For each = 0, 1,..., k 1, we deote by H the evet that a sequece of trals the outcome S occurs at the last trals. I artcular, H 0 meas that the outcome F occurs at the last tral. Let u ( be the robablty of H. For = 0, 1,..., k 2, the trasto {}}{}... F {{ S... S} +1 {}}{.}.. F S {{... SS} +1 haes wth robablty, hece u (+1 +1 = u ( q = 1, we have +1 = (1 ( + u (1 the followg system of recurrece relatos: +1 = (1 ( + u (1 u (1 +1 =, u (2 +1 = u (1,... u (k 1 +1 = u (k 2. For k 1, we ut v = u (k 1. The u (1. Sce the robablty of F s u (k 1. Thus, we obta + + u (k 1 = 1 u(1 +1 = 1 u ( = = 1 u (k 1 k 1 +k 1 = 1 = 1 u(2 +1 = = 1 u (k 1 2 +k 2 = 1 v k 2 +k 2,... u (k 1 = v, whch mles that +1 = 1 k 1 v +k, v +k = (1 k 1 ( v+k 1 k 1 + v +k 2 k 2, k 1 v +k 1, + + v. Dvdg both sdes of the equato obtaed by, we obta ( v +k v+k 1 = (1 +k 1 + v +k 2 +k v. +k 2

3 Alcato of geeratg fuctos 2493 Puttg x = v, we ca rereset the last relato the form hece x +k = (1 (x +k 1 + x +k x, x +k = 1 (x +k 1 + x +k x. (1 If = 1/2, the relato (1 has the form x +k = x +k 1 + x +k x, whch, for k = 2, cocdes wth the recurrece relato for Fboacc umbers. Relato (1 s roved for k 1. For = 0, 1,..., k 2, we ut x = 0 ad calculate the values of x at = k 1, k,..., 2k 1. By defto, we = P ( H k 1. The evet H k 1 k 1 cossts of Therefore, ts robablty s equal to k 1, ad so, x k 1 = 1. If k 2k 1, the the evet H k 1 cossts of have x = v = u (k 1 oe sequece S... S of legth k 1. k {}}{ the sequeces of the form }... F{{ S... S}, where dots at the begg mea F s or S s. Cosequetly, P ( H k 1 = (1 k 1, ad x = (1 k 1 for = k, k + 1,..., 2k 1. Lemma 2.1. Relato (1 s vald for all tegers 0. Proof. For = 0, we have x k = (1 / x k 1. Ths relato s vald sce x k = (1 / ad x k 1 = 1. If 1 k 1, the k k 2k 1. Therefore, x +k = (1 1. Let us calculate the rght-had sde of equato (1. We have x +k 1 + x +k x = = 1 = = 1. Cosequetly, the rght-had sde of equato (1 s equal to (1 1 = (1 1 = x +k. Lemma 2.2. The geeratg fucto of the sequece x s gve by the formula ϕ(t = t k (t + t t k = (tk 1 tk (1 t k+1 t +. (2

4 2494 B.M. Bekker, O.A. Ivaov, ad V.V. Ivaova Proof. By defto, ϕ(t = =k 1 x t. Removg brackets (x k 1 t k 1 + x k t k + ( 1 1 (t + t2 + + t k, we obta by relato (1 that x k 1 t k 1 + ( x k 1 whch mles equato (2. x k 1 t k + ( x k+1 1 (x k + x k 1 t k ( x 2k 2 1 (x 2k x k 1 t 2k 2 + ( x +k 1 (x +k x t +k + = t k 1, Lemma 2.3. We have G X (t = tϕ(t, where ϕ(t s the geeratg fucto of the sequece x. Proof. We ote that the robablty that k successve evets h occur the frst tme mmedately after the th tral Beroull s scheme s the roduct of ad the robablty of H 1. k 1 Thus, P (X = = P ( H 1 k 1 = u k 1 1 = v 1 = x 1. Therefore, G X (t = P (X = t = =k x 1 t = t =k =k 1 x (t = tϕ(t. I cocluso, we derve exlct formulas for the terms of the sequece x. We cosder the olyomal g(z = z k 1 (z k 1 + z k Let z 1, z 2,..., z k be the comlex roots of g(z, ad let a = k =1 z g (z. Sce g(z = (z z 1 (z z 2... (z z k, we have the relatos a 0 = a 1 = = a k 2 = 0 ad a k 1 = 1. Sce z are the roots of g(z, we obta z +k = z z k = 1 ( z +k 1 + z +k z,

5 Alcato of geeratg fuctos 2495 whch mles the relato a +k = 1 (a +k 1 + a +k a. Therefore, the umbers a satsfy the same kth order recurrece relatos as the umbers x do. Takg to accout that the frst k terms of the sequeces questo cocde, we see that x = a for all 0. As a corollary, we obta the followg exlct formula for the terms of the sequece x : x = k =1 z g (z. (3 Now we use formula (5 from the aer [1]. Let w be the comlete homogeeous olyomal of degree k varables. We ut, by defto, w 0 = 1 ad w 1 = w 2 = = w 1 k = 0. By Theorem 1 of the aer [1], we have the relato k z +k 1 = w g (z 1, z 2,..., z k, (z =1 from whch we obta by (3 that x = w k+1 (z 1, z 2,..., z k. Ackowledgemets. The frst amed author was artally suorted by the Russa Foudato for Basc Research (grat o Refereces [1] B. M. Bekker, O. A. Ivaov ad A. S. Merkurjev, A Algebrac Idetty ad the Jacob Trud Formula, Vestk St. Petersburg Uversty: Mathematcs, 49 (2016, o. 1, 1-4. htt://dx.do.org/ /s [2] L.M. Chaves ad D.J. de Souza, Watg tme for a ru of N successes Beroull sequeces, Rev. Bras. Bom., São Paulo, 25 (2007, o. 4, [3] W. Feller, A Itroducto to Probablty Theory ad Its Alcatos, Vol. 1, 3rd ed., Joh Wley & Sos, New York, [4] A.N. Phlou ad A.A. Muwaf, Watg for Kth cosecutve success ad the Fboacc sequece of order K, Fboacc Quart., 20 (1982, o. 1, Receved: July 6, 2016; Publshed: August 14, 2016

On the Rational Valued Characters Table of the

On the Rational Valued Characters Table of the Aled Mathematcal Sceces, Vol., 7, o. 9, 95-9 HIKARI Ltd, www.m-hkar.com htts://do.or/.9/ams.7.7576 O the Ratoal Valued Characters Table of the Grou (Q m C Whe m s a Eve Number Raaa Hassa Abass Deartmet

More information

Journal Of Inequalities And Applications, 2008, v. 2008, p

Journal Of Inequalities And Applications, 2008, v. 2008, p Ttle O verse Hlbert-tye equaltes Authors Chagja, Z; Cheug, WS Ctato Joural Of Iequaltes Ad Alcatos, 2008, v. 2008,. 693248 Issued Date 2008 URL htt://hdl.hadle.et/0722/56208 Rghts Ths work s lcesed uder

More information

Random Variables. ECE 313 Probability with Engineering Applications Lecture 8 Professor Ravi K. Iyer University of Illinois

Random Variables. ECE 313 Probability with Engineering Applications Lecture 8 Professor Ravi K. Iyer University of Illinois Radom Varables ECE 313 Probablty wth Egeerg Alcatos Lecture 8 Professor Rav K. Iyer Uversty of Illos Iyer - Lecture 8 ECE 313 Fall 013 Today s Tocs Revew o Radom Varables Cumulatve Dstrbuto Fucto (CDF

More information

Asymptotic Formulas Composite Numbers II

Asymptotic Formulas Composite Numbers II Iteratoal Matematcal Forum, Vol. 8, 203, o. 34, 65-662 HIKARI Ltd, www.m-kar.com ttp://d.do.org/0.2988/mf.203.3854 Asymptotc Formulas Composte Numbers II Rafael Jakmczuk Dvsó Matemátca, Uversdad Nacoal

More information

On the Behavior of Positive Solutions of a Difference. equation system:

On the Behavior of Positive Solutions of a Difference. equation system: Aled Mathematcs -8 htt://d.do.org/.6/am..9a Publshed Ole Setember (htt://www.scr.org/joural/am) O the Behavor of Postve Solutos of a Dfferece Equatos Sstem * Decu Zhag Weqag J # Lg Wag Xaobao L Isttute

More information

2. Independence and Bernoulli Trials

2. Independence and Bernoulli Trials . Ideedece ad Beroull Trals Ideedece: Evets ad B are deedet f B B. - It s easy to show that, B deedet mles, B;, B are all deedet ars. For examle, ad so that B or B B B B B φ,.e., ad B are deedet evets.,

More information

A new Family of Distributions Using the pdf of the. rth Order Statistic from Independent Non- Identically Distributed Random Variables

A new Family of Distributions Using the pdf of the. rth Order Statistic from Independent Non- Identically Distributed Random Variables Iteratoal Joural of Cotemporary Mathematcal Sceces Vol. 07 o. 8 9-05 HIKARI Ltd www.m-hkar.com https://do.org/0.988/jcms.07.799 A ew Famly of Dstrbutos Usg the pdf of the rth Order Statstc from Idepedet

More information

On quaternions with generalized Fibonacci and Lucas number components

On quaternions with generalized Fibonacci and Lucas number components Polatl Kesm Advaces Dfferece Equatos (205) 205:69 DOI 0.86/s3662-05-05-x R E S E A R C H Ope Access O quateros wth geeralzed Fboacc Lucas umber compoets Emrah Polatl * Seyhu Kesm * Correspodece: emrah.polatl@beu.edu.tr

More information

Mu Sequences/Series Solutions National Convention 2014

Mu Sequences/Series Solutions National Convention 2014 Mu Sequeces/Seres Solutos Natoal Coveto 04 C 6 E A 6C A 6 B B 7 A D 7 D C 7 A B 8 A B 8 A C 8 E 4 B 9 B 4 E 9 B 4 C 9 E C 0 A A 0 D B 0 C C Usg basc propertes of arthmetc sequeces, we fd a ad bm m We eed

More information

Fibonacci Identities as Binomial Sums

Fibonacci Identities as Binomial Sums It. J. Cotemp. Math. Sceces, Vol. 7, 1, o. 38, 1871-1876 Fboacc Idettes as Bomal Sums Mohammad K. Azara Departmet of Mathematcs, Uversty of Evasvlle 18 Lcol Aveue, Evasvlle, IN 477, USA E-mal: azara@evasvlle.edu

More information

Random Variables and Probability Distributions

Random Variables and Probability Distributions Radom Varables ad Probablty Dstrbutos * If X : S R s a dscrete radom varable wth rage {x, x, x 3,. } the r = P (X = xr ) = * Let X : S R be a dscrete radom varable wth rage {x, x, x 3,.}.If x r P(X = x

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

#A27 INTEGERS 13 (2013) SOME WEIGHTED SUMS OF PRODUCTS OF LUCAS SEQUENCES

#A27 INTEGERS 13 (2013) SOME WEIGHTED SUMS OF PRODUCTS OF LUCAS SEQUENCES #A27 INTEGERS 3 (203) SOME WEIGHTED SUMS OF PRODUCTS OF LUCAS SEQUENCES Emrah Kılıç Mathematcs Departmet, TOBB Uversty of Ecoomcs ad Techology, Akara, Turkey eklc@etu.edu.tr Neşe Ömür Mathematcs Departmet,

More information

Lecture 9. Some Useful Discrete Distributions. Some Useful Discrete Distributions. The observations generated by different experiments have

Lecture 9. Some Useful Discrete Distributions. Some Useful Discrete Distributions. The observations generated by different experiments have NM 7 Lecture 9 Some Useful Dscrete Dstrbutos Some Useful Dscrete Dstrbutos The observatos geerated by dfferet eermets have the same geeral tye of behavor. Cosequetly, radom varables assocated wth these

More information

å 1 13 Practice Final Examination Solutions - = CS109 Dec 5, 2018

å 1 13 Practice Final Examination Solutions - = CS109 Dec 5, 2018 Chrs Pech Fal Practce CS09 Dec 5, 08 Practce Fal Examato Solutos. Aswer: 4/5 8/7. There are multle ways to obta ths aswer; here are two: The frst commo method s to sum over all ossbltes for the rak of

More information

Parameter, Statistic and Random Samples

Parameter, Statistic and Random Samples Parameter, Statstc ad Radom Samples A parameter s a umber that descrbes the populato. It s a fxed umber, but practce we do ot kow ts value. A statstc s a fucto of the sample data,.e., t s a quatty whose

More information

Optimum Probability Distribution for Minimum Redundancy of Source Coding

Optimum Probability Distribution for Minimum Redundancy of Source Coding Aled Mathematcs, 04, 5, 96-05 Publshed Ole Jauary 04 (htt://www.scr.org/oural/am) htt://dx.do.org/0.436/am.04.50 Otmum Probablty strbuto for Mmum Redudacy of Source Codg Om Parkash, Pryaka Kakkar eartmet

More information

Channel Models with Memory. Channel Models with Memory. Channel Models with Memory. Channel Models with Memory

Channel Models with Memory. Channel Models with Memory. Channel Models with Memory. Channel Models with Memory Chael Models wth Memory Chael Models wth Memory Hayder radha Electrcal ad Comuter Egeerg Mchga State Uversty I may ractcal etworkg scearos (cludg the Iteret ad wreless etworks), the uderlyg chaels are

More information

Law of Large Numbers

Law of Large Numbers Toss a co tmes. Law of Large Numbers Suppose 0 f f th th toss came up H toss came up T s are Beroull radom varables wth p ½ ad E( ) ½. The proporto of heads s. Itutvely approaches ½ as. week 2 Markov s

More information

The k-nacci triangle and applications

The k-nacci triangle and applications Kuhapataakul & Aataktpasal, Coget Mathematcs 7, : 9 https://doorg/8/879 PURE MATHEMATICS RESEARCH ARTICLE The k-acc tragle ad applcatos Katapho Kuhapataakul * ad Porpawee Aataktpasal Receved: March 7 Accepted:

More information

On the Interval Zoro Symmetric Single Step. Procedure IZSS1-5D for the Simultaneous. Bounding of Real Polynomial Zeros

On the Interval Zoro Symmetric Single Step. Procedure IZSS1-5D for the Simultaneous. Bounding of Real Polynomial Zeros It. Joural of Math. Aalyss, Vol. 7, 2013, o. 59, 2947-2951 HIKARI Ltd, www.m-hkar.com http://dx.do.org/10.12988/ma.2013.310259 O the Iterval Zoro Symmetrc Sgle Step Procedure IZSS1-5D for the Smultaeous

More information

D KL (P Q) := p i ln p i q i

D KL (P Q) := p i ln p i q i Cheroff-Bouds 1 The Geeral Boud Let P 1,, m ) ad Q q 1,, q m ) be two dstrbutos o m elemets, e,, q 0, for 1,, m, ad m 1 m 1 q 1 The Kullback-Lebler dvergece or relatve etroy of P ad Q s defed as m D KL

More information

THE PUBLISHING HOUSE PROCEEDINGS OF THE ROMANIAN ACADEMY, Series A, OF THE ROMANIAN ACADEMY Volume 9, Number 3/2008, pp

THE PUBLISHING HOUSE PROCEEDINGS OF THE ROMANIAN ACADEMY, Series A, OF THE ROMANIAN ACADEMY Volume 9, Number 3/2008, pp THE PUBLISHIN HOUSE PROCEEDINS OF THE ROMANIAN ACADEMY, Seres A, OF THE ROMANIAN ACADEMY Volume 9, Number 3/8, THE UNITS IN Stela Corelu ANDRONESCU Uversty of Pteşt, Deartmet of Mathematcs, Târgu Vale

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

Homework 1: Solutions Sid Banerjee Problem 1: (Practice with Asymptotic Notation) ORIE 4520: Stochastics at Scale Fall 2015

Homework 1: Solutions Sid Banerjee Problem 1: (Practice with Asymptotic Notation) ORIE 4520: Stochastics at Scale Fall 2015 Fall 05 Homework : Solutos Problem : (Practce wth Asymptotc Notato) A essetal requremet for uderstadg scalg behavor s comfort wth asymptotc (or bg-o ) otato. I ths problem, you wll prove some basc facts

More information

On Modified Interval Symmetric Single-Step Procedure ISS2-5D for the Simultaneous Inclusion of Polynomial Zeros

On Modified Interval Symmetric Single-Step Procedure ISS2-5D for the Simultaneous Inclusion of Polynomial Zeros It. Joural of Math. Aalyss, Vol. 7, 2013, o. 20, 983-988 HIKARI Ltd, www.m-hkar.com O Modfed Iterval Symmetrc Sgle-Step Procedure ISS2-5D for the Smultaeous Icluso of Polyomal Zeros 1 Nora Jamalud, 1 Masor

More information

IS 709/809: Computational Methods in IS Research. Simple Markovian Queueing Model

IS 709/809: Computational Methods in IS Research. Simple Markovian Queueing Model IS 79/89: Comutatoal Methods IS Research Smle Marova Queueg Model Nrmalya Roy Deartmet of Iformato Systems Uversty of Marylad Baltmore Couty www.umbc.edu Queueg Theory Software QtsPlus software The software

More information

Research Article Gauss-Lobatto Formulae and Extremal Problems

Research Article Gauss-Lobatto Formulae and Extremal Problems Hdaw Publshg Corporato Joural of Iequaltes ad Applcatos Volume 2008 Artcle ID 624989 0 pages do:055/2008/624989 Research Artcle Gauss-Lobatto Formulae ad Extremal Problems wth Polyomals Aa Mara Acu ad

More information

STRONG CONSISTENCY FOR SIMPLE LINEAR EV MODEL WITH v/ -MIXING

STRONG CONSISTENCY FOR SIMPLE LINEAR EV MODEL WITH v/ -MIXING Joural of tatstcs: Advaces Theory ad Alcatos Volume 5, Number, 6, Pages 3- Avalable at htt://scetfcadvaces.co. DOI: htt://d.do.org/.864/jsata_7678 TRONG CONITENCY FOR IMPLE LINEAR EV MODEL WITH v/ -MIXING

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 Fuzzy Probability Measures

Two Fuzzy Probability Measures Two Fuzzy robablty Measures Zdeěk Karíšek Isttute of Mathematcs Faculty of Mechacal Egeerg Bro Uversty of Techology Techcká 2 66 69 Bro Czech Reublc e-mal: karsek@umfmevutbrcz Karel Slavíček System dmstrato

More information

arxiv: v4 [math.nt] 14 Aug 2015

arxiv: v4 [math.nt] 14 Aug 2015 arxv:52.799v4 [math.nt] 4 Aug 25 O the propertes of terated bomal trasforms for the Padova ad Perr matrx sequeces Nazmye Ylmaz ad Necat Tasara Departmet of Mathematcs, Faculty of Scece, Selcu Uversty,

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

Factorization of Finite Abelian Groups

Factorization of Finite Abelian Groups Iteratoal Joural of Algebra, Vol 6, 0, o 3, 0-07 Factorzato of Fte Abela Grous Khald Am Uversty of Bahra Deartmet of Mathematcs PO Box 3038 Sakhr, Bahra kamee@uobedubh Abstract If G s a fte abela grou

More information

GENERALIZATIONS OF CEVA S THEOREM AND APPLICATIONS

GENERALIZATIONS OF CEVA S THEOREM AND APPLICATIONS GENERLIZTIONS OF CEV S THEOREM ND PPLICTIONS Floret Smaradache Uversty of New Mexco 200 College Road Gallup, NM 87301, US E-mal: smarad@um.edu I these paragraphs oe presets three geeralzatos of the famous

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

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

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

Extend the Borel-Cantelli Lemma to Sequences of. Non-Independent Random Variables

Extend the Borel-Cantelli Lemma to Sequences of. Non-Independent Random Variables ppled Mathematcal Sceces, Vol 4, 00, o 3, 637-64 xted the Borel-Catell Lemma to Sequeces of No-Idepedet Radom Varables olah Der Departmet of Statstc, Scece ad Research Campus zad Uversty of Tehra-Ira der53@gmalcom

More information

Pr[X (p + t)n] e D KL(p+t p)n.

Pr[X (p + t)n] e D KL(p+t p)n. Cheroff Bouds Wolfgag Mulzer 1 The Geeral Boud Let P 1,..., m ) ad Q q 1,..., q m ) be two dstrbutos o m elemets,.e.,, q 0, for 1,..., m, ad m 1 m 1 q 1. The Kullback-Lebler dvergece or relatve etroy of

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

Analysis of System Performance IN2072 Chapter 5 Analysis of Non Markov Systems

Analysis of System Performance IN2072 Chapter 5 Analysis of Non Markov Systems Char for Network Archtectures ad Servces Prof. Carle Departmet of Computer Scece U Müche Aalyss of System Performace IN2072 Chapter 5 Aalyss of No Markov Systems Dr. Alexader Kle Prof. Dr.-Ig. Georg Carle

More information

It is Advantageous to Make a Syllabus as Precise as Possible: Decision-Theoretic Analysis

It is Advantageous to Make a Syllabus as Precise as Possible: Decision-Theoretic Analysis Joural of Iovatve Techology ad Educato, Vol. 4, 2017, o. 1, 1-5 HIKARI Ltd, www.m-hkar.com https://do.org/10.12988/jte.2017.61146 It s Advatageous to Make a Syllabus as Precse as Possble: Decso-Theoretc

More information

The Occupancy and Coupon Collector problems

The Occupancy and Coupon Collector problems Chapter 4 The Occupacy ad Coupo Collector problems By Sarel Har-Peled, Jauary 9, 08 4 Prelmares [ Defto 4 Varace ad Stadard Devato For a radom varable X, let V E [ X [ µ X deote the varace of X, where

More information

Bivariate Vieta-Fibonacci and Bivariate Vieta-Lucas Polynomials

Bivariate Vieta-Fibonacci and Bivariate Vieta-Lucas Polynomials IOSR Joural of Mathematcs (IOSR-JM) e-issn: 78-78, p-issn: 19-76X. Volume 1, Issue Ver. II (Jul. - Aug.016), PP -0 www.osrjourals.org Bvarate Veta-Fboacc ad Bvarate Veta-Lucas Polomals E. Gokce KOCER 1

More information

A Family of Non-Self Maps Satisfying i -Contractive Condition and Having Unique Common Fixed Point in Metrically Convex Spaces *

A Family of Non-Self Maps Satisfying i -Contractive Condition and Having Unique Common Fixed Point in Metrically Convex Spaces * Advaces Pure Matheatcs 0 80-84 htt://dxdoorg/0436/a04036 Publshed Ole July 0 (htt://wwwscrporg/oural/a) A Faly of No-Self Mas Satsfyg -Cotractve Codto ad Havg Uque Coo Fxed Pot Metrcally Covex Saces *

More information

Research Article Multidimensional Hilbert-Type Inequalities with a Homogeneous Kernel

Research Article Multidimensional Hilbert-Type Inequalities with a Homogeneous Kernel Hdaw Publshg Corporato Joural of Iequaltes ad Applcatos Volume 29, Artcle ID 3958, 2 pages do:.55/29/3958 Research Artcle Multdmesoal Hlbert-Type Iequaltes wth a Homogeeous Kerel Predrag Vuovć Faculty

More information

2SLS Estimates ECON In this case, begin with the assumption that E[ i

2SLS Estimates ECON In this case, begin with the assumption that E[ i SLS Estmates ECON 3033 Bll Evas Fall 05 Two-Stage Least Squares (SLS Cosder a stadard lear bvarate regresso model y 0 x. I ths case, beg wth the assumto that E[ x] 0 whch meas that OLS estmates of wll

More information

IFYMB002 Mathematics Business Appendix C Formula Booklet

IFYMB002 Mathematics Business Appendix C Formula Booklet Iteratoal Foudato Year (IFY IFYMB00 Mathematcs Busess Apped C Formula Booklet Related Documet: IFY Mathematcs Busess Syllabus 07/8 IFYMB00 Maths Busess Apped C Formula Booklet Cotets lease ote that the

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

Lebesgue Measure of Generalized Cantor Set

Lebesgue Measure of Generalized Cantor Set Aals of Pure ad Appled Mathematcs Vol., No.,, -8 ISSN: -8X P), -888ole) Publshed o 8 May www.researchmathsc.org Aals of Lebesgue Measure of Geeralzed ator Set Md. Jahurul Islam ad Md. Shahdul Islam Departmet

More information

Discrete Mathematics and Probability Theory Fall 2016 Seshia and Walrand DIS 10b

Discrete Mathematics and Probability Theory Fall 2016 Seshia and Walrand DIS 10b CS 70 Dscrete Mathematcs ad Probablty Theory Fall 206 Sesha ad Walrad DIS 0b. Wll I Get My Package? Seaky delvery guy of some compay s out delverg packages to customers. Not oly does he had a radom package

More information

Lecture 02: Bounding tail distributions of a random variable

Lecture 02: Bounding tail distributions of a random variable CSCI-B609: A Theorst s Toolkt, Fall 206 Aug 25 Lecture 02: Boudg tal dstrbutos of a radom varable Lecturer: Yua Zhou Scrbe: Yua Xe & Yua Zhou Let us cosder the ubased co flps aga. I.e. let the outcome

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

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

ON BIVARIATE GEOMETRIC DISTRIBUTION. K. Jayakumar, D.A. Mundassery 1. INTRODUCTION

ON BIVARIATE GEOMETRIC DISTRIBUTION. K. Jayakumar, D.A. Mundassery 1. INTRODUCTION STATISTICA, ao LXVII, 4, 007 O BIVARIATE GEOMETRIC DISTRIBUTIO ITRODUCTIO Probablty dstrbutos of radom sums of deedetly ad detcally dstrbuted radom varables are maly aled modelg ractcal roblems that deal

More information

Minimizing Total Completion Time in a Flow-shop Scheduling Problems with a Single Server

Minimizing Total Completion Time in a Flow-shop Scheduling Problems with a Single Server Joural of Aled Mathematcs & Boformatcs vol. o.3 0 33-38 SSN: 79-660 (rt) 79-6939 (ole) Sceress Ltd 0 Mmzg Total omleto Tme a Flow-sho Schedulg Problems wth a Sgle Server Sh lg ad heg xue-guag Abstract

More information

Lecture 4 Sep 9, 2015

Lecture 4 Sep 9, 2015 CS 388R: Radomzed Algorthms Fall 205 Prof. Erc Prce Lecture 4 Sep 9, 205 Scrbe: Xagru Huag & Chad Voegele Overvew I prevous lectures, we troduced some basc probablty, the Cheroff boud, the coupo collector

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

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

Can we take the Mysticism Out of the Pearson Coefficient of Linear Correlation?

Can we take the Mysticism Out of the Pearson Coefficient of Linear Correlation? Ca we tae the Mstcsm Out of the Pearso Coeffcet of Lear Correlato? Itroducto As the ttle of ths tutoral dcates, our purpose s to egeder a clear uderstadg of the Pearso coeffcet of lear correlato studets

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

A New Method for Decision Making Based on Soft Matrix Theory

A New Method for Decision Making Based on Soft Matrix Theory Joural of Scetfc esearch & eports 3(5): 0-7, 04; rtcle o. JS.04.5.00 SCIENCEDOMIN teratoal www.scecedoma.org New Method for Decso Mag Based o Soft Matrx Theory Zhmg Zhag * College of Mathematcs ad Computer

More information

h-analogue of Fibonacci Numbers

h-analogue of Fibonacci Numbers h-aalogue of Fboacc Numbers arxv:090.0038v [math-ph 30 Sep 009 H.B. Beaoum Prce Mohammad Uversty, Al-Khobar 395, Saud Araba Abstract I ths paper, we troduce the h-aalogue of Fboacc umbers for o-commutatve

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

On the characteristics of partial differential equations

On the characteristics of partial differential equations Sur les caractérstques des équatos au dérvées artelles Bull Soc Math Frace 5 (897) 8- O the characterstcs of artal dfferetal equatos By JULES BEUDON Traslated by D H Delhech I a ote that was reseted to

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

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

Semi-Riemann Metric on. the Tangent Bundle and its Index

Semi-Riemann Metric on. the Tangent Bundle and its Index t J Cotem Math Sceces ol 5 o 3 33-44 Sem-Rema Metrc o the Taet Budle ad ts dex smet Ayha Pamuale Uversty Educato Faculty Dezl Turey ayha@auedutr Erol asar Mers Uversty Art ad Scece Faculty 33343 Mers Turey

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

Waiting Time Distribution of Demand Requiring Multiple Items under a Base Stock Policy

Waiting Time Distribution of Demand Requiring Multiple Items under a Base Stock Policy Joural of Servce Scece ad Maagemet 23 6 266-272 http://d.do.org/.4236/jssm.23.643 Publshed Ole October 23 (http://www.scrp.org/joural/jssm) Watg Tme Dstrbuto of Demad Requrg Multple Items uder a Base Stoc

More information

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

NP!= P. By Liu Ran. Table of Contents. The P vs. NP problem is a major unsolved problem in computer NP!= P By Lu Ra Table of Cotets. Itroduce 2. Strategy 3. Prelmary theorem 4. Proof 5. Expla 6. Cocluso. Itroduce The P vs. NP problem s a major usolved problem computer scece. Iformally, t asks whether

More information

Solving Constrained Flow-Shop Scheduling. Problems with Three Machines

Solving Constrained Flow-Shop Scheduling. Problems with Three Machines It J Cotemp Math Sceces, Vol 5, 2010, o 19, 921-929 Solvg Costraed Flow-Shop Schedulg Problems wth Three Maches P Pada ad P Rajedra Departmet of Mathematcs, School of Advaced Sceces, VIT Uversty, Vellore-632

More information

UNIVERSITY OF OSLO DEPARTMENT OF ECONOMICS

UNIVERSITY OF OSLO DEPARTMENT OF ECONOMICS UNIVERSITY OF OSLO DEPARTMENT OF ECONOMICS Exam: ECON430 Statstcs Date of exam: Frday, December 8, 07 Grades are gve: Jauary 4, 08 Tme for exam: 0900 am 00 oo The problem set covers 5 pages Resources allowed:

More information

Lecture Notes Types of economic variables

Lecture Notes Types of economic variables Lecture Notes 3 1. Types of ecoomc varables () Cotuous varable takes o a cotuum the sample space, such as all pots o a le or all real umbers Example: GDP, Polluto cocetrato, etc. () Dscrete varables fte

More information

About k-perfect numbers

About k-perfect numbers DOI: 0.47/auom-04-0005 A. Şt. Uv. Ovdus Costaţa Vol.,04, 45 50 About k-perfect umbers Mhály Becze Abstract ABSTRACT. I ths paper we preset some results about k-perfect umbers, ad geeralze two equaltes

More information

THE ROYAL STATISTICAL SOCIETY GRADUATE DIPLOMA

THE ROYAL STATISTICAL SOCIETY GRADUATE DIPLOMA THE ROYAL STATISTICAL SOCIETY 3 EXAMINATIONS SOLUTIONS GRADUATE DIPLOMA PAPER I STATISTICAL THEORY & METHODS The Socety provdes these solutos to assst caddates preparg for the examatos future years ad

More information

L Inequalities for Polynomials

L Inequalities for Polynomials Aled Mathematcs 3-38 do:436/am338 Publshed Ole March (htt://wwwscrorg/oural/am) L Iequaltes for Polyomals Abstract Abdul A Nsar A Rather Deartmet of Mathematcs Kashmr Uversty Sragar Ida E-mal: drarather@gmalcom

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

f f... f 1 n n (ii) Median : It is the value of the middle-most observation(s).

f f... f 1 n n (ii) Median : It is the value of the middle-most observation(s). CHAPTER STATISTICS Pots to Remember :. Facts or fgures, collected wth a defte pupose, are called Data.. Statstcs s the area of study dealg wth the collecto, presetato, aalyss ad terpretato of data.. The

More information

Comparing Different Estimators of three Parameters for Transmuted Weibull Distribution

Comparing Different Estimators of three Parameters for Transmuted Weibull Distribution Global Joural of Pure ad Appled Mathematcs. ISSN 0973-768 Volume 3, Number 9 (207), pp. 55-528 Research Ida Publcatos http://www.rpublcato.com Comparg Dfferet Estmators of three Parameters for Trasmuted

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

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

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

Chain Rules for Entropy

Chain Rules for Entropy Cha Rules for Etroy The etroy of a collecto of radom varables s the sum of codtoal etroes. Theorem: Let be radom varables havg the mass robablty x x.x. The...... The roof s obtaed by reeatg the alcato

More information

UNIVERSITY OF OSLO DEPARTMENT OF ECONOMICS

UNIVERSITY OF OSLO DEPARTMENT OF ECONOMICS UNIVERSITY OF OSLO DEPARTMENT OF ECONOMICS Postpoed exam: ECON430 Statstcs Date of exam: Jauary 0, 0 Tme for exam: 09:00 a.m. :00 oo The problem set covers 5 pages Resources allowed: All wrtte ad prted

More information

Simulation Output Analysis

Simulation Output Analysis Smulato Output Aalyss Summary Examples Parameter Estmato Sample Mea ad Varace Pot ad Iterval Estmato ermatg ad o-ermatg Smulato Mea Square Errors Example: Sgle Server Queueg System x(t) S 4 S 4 S 3 S 5

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

Analysis of Variance with Weibull Data

Analysis of Variance with Weibull Data Aalyss of Varace wth Webull Data Lahaa Watthaacheewaul Abstract I statstcal data aalyss by aalyss of varace, the usual basc assumptos are that the model s addtve ad the errors are radomly, depedetly, ad

More information

STK3100 and STK4100 Autumn 2017

STK3100 and STK4100 Autumn 2017 SK3 ad SK4 Autum 7 Geeralzed lear models Part III Covers the followg materal from chaters 4 ad 5: Sectos 4..5, 4.3.5, 4.3.6, 4.4., 4.4., ad 4.4.3 Sectos 5.., 5.., ad 5.5. Ørulf Borga Deartmet of Mathematcs

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

02/15/04 INTERESTING FINITE AND INFINITE PRODUCTS FROM SIMPLE ALGEBRAIC IDENTITIES

02/15/04 INTERESTING FINITE AND INFINITE PRODUCTS FROM SIMPLE ALGEBRAIC IDENTITIES 0/5/04 ITERESTIG FIITE AD IFIITE PRODUCTS FROM SIMPLE ALGEBRAIC IDETITIES Thomas J Osler Mathematcs Departmet Rowa Uversty Glassboro J 0808 Osler@rowaedu Itroducto The dfferece of two squares, y = + y

More information

Some queue models with different service rates. Július REBO, Žilinská univerzita, DP Prievidza

Some queue models with different service rates. Július REBO, Žilinská univerzita, DP Prievidza Some queue models wth dfferet servce rates Júlus REBO, Žlsá uverzta, DP Prevdza Itroducto: They are well ow models the queue theory Kedall s classfcato deoted as M/M//N wth equal rates of servce each servce

More information

Introduction to local (nonparametric) density estimation. methods

Introduction to local (nonparametric) density estimation. methods Itroducto to local (oparametrc) desty estmato methods A slecture by Yu Lu for ECE 66 Sprg 014 1. Itroducto Ths slecture troduces two local desty estmato methods whch are Parze desty estmato ad k-earest

More information

Lower and upper bound for parametric Useful R-norm information measure

Lower and upper bound for parametric Useful R-norm information measure Iteratoal Joral of Statstcs ad Aled Mathematcs 206; (3): 6-20 ISS: 2456-452 Maths 206; (3): 6-20 206 Stats & Maths wwwmathsjoralcom eceved: 04-07-206 Acceted: 05-08-206 haesh Garg Satsh Kmar ower ad er

More information

Victor Adamchik. Wolfram Research Inc., 100 Trade Center Dr., October 21, 1996

Victor Adamchik. Wolfram Research Inc., 100 Trade Center Dr., October 21, 1996 O Strlg umbers ad Euler sums Vctor Adamch Wolfram Research Ic., Trade Ceter Dr., Chamag, IL 68, USA October, 996 Abstract. I ths aer, we roose the aother yet geeralzato of Strlg umbers of the rst d for

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

Lecture 7. Confidence Intervals and Hypothesis Tests in the Simple CLR Model

Lecture 7. Confidence Intervals and Hypothesis Tests in the Simple CLR Model Lecture 7. Cofdece Itervals ad Hypothess Tests the Smple CLR Model I lecture 6 we troduced the Classcal Lear Regresso (CLR) model that s the radom expermet of whch the data Y,,, K, are the outcomes. The

More information

Some results and conjectures about recurrence relations for certain sequences of binomial sums.

Some results and conjectures about recurrence relations for certain sequences of binomial sums. Soe results ad coectures about recurrece relatos for certa sequeces of boal sus Joha Cgler Faultät für Matheat Uverstät We A-9 We Nordbergstraße 5 Joha Cgler@uveacat Abstract I a prevous paper [] I have

More information

Sebastián Martín Ruiz. Applications of Smarandache Function, and Prime and Coprime Functions

Sebastián Martín Ruiz. Applications of Smarandache Function, and Prime and Coprime Functions Sebastá Martí Ruz Alcatos of Saradache Fucto ad Pre ad Core Fuctos 0 C L f L otherwse are core ubers Aerca Research Press Rehoboth 00 Sebastá Martí Ruz Avda. De Regla 43 Choa 550 Cadz Sa Sarada@telele.es

More information