Maximum Walk Entropy Implies Walk Regularity
|
|
- Grant Marcus Farmer
- 5 years ago
- Views:
Transcription
1 Maxmum Walk Etropy Imples Walk Regularty Eresto Estraa, a José. e la Peña Departmet of Mathematcs a Statstcs, Uversty of Strathclye, Glasgow G XH, U.K., CIMT, Guaajuato, Mexco BSTRCT: The oto of walk etropy S, G for a graph G at the verse temperature was put forwar recetly by Estraa et al. (4) [6]. It was further prove by Bez [] that a graph s walk-regular f a oly f ts walk etropy s maxmum for all temperatures. Bez (4) [] cojecture that walk regularty ca be characterze by the walk etropy f a oly f there s a, such that S, f a oly f the S G, l. We also prove that f the graph s regular but ot walk- regular G s maxmum. Here we prove that a graph s walk regular S G, l for every graph s ot regular the a lm S G, l lm S G, S G, l for every for some.. If the MSC: 5C5; 56; 8C Keywors: Walk-regularty; Graph etropes; Graph walks. Itroucto. The cocept of walk etropy was recetly propose as a way of characterzg graphs usg statstcal mechacs cocepts [6]. For a smple, urecte graph G, E oes a ajacecy matrx the walk etropy s efe as S G, p l p, wth
2 where p e a Z ( k B s the Boltzma costat a T the absolute kt B temperature). Here Z Tr e represets the partto fucto of the graph, frequetly referre the lterature as the Estraa ex of the graph [3, 4, 9]. The term e represets the weghte cotrbuto of every subgraph to the cetralty of the correspog oe, kow as the subgraph cetralty SC of the oe [7, 5, 8]. The walk etropy calle mmeately the atteto the lterature [] ue to ts may terestg mathematcal propertes as well as ts potetals for characterzg graphs a etworks. I [6] the authors state a cojecture whch was subsequetly prove by Bez [] as the followg Theorem.. [] graph s walk-regular f a oly f S G, l for all. Bez [] also reformulate aother cojecture state by Estraa et al. [6] the followg stroger form Cojecture.. [] graph s walk-regular f a oly f there exsts a such that S G, l. followg thr cojecture to be cosere here was orgally state by Estraa et al. [6] as the Cojecture.3. Let G be a o-regular graph, the S G, l for every. I ths ote we prove these two cojectures, whch mmeately mply that the walketropy s a strog characterzato of the walk-regularty graphs a also gves strog mathematcal support to the stregth of ths graph varat for stuyg the structure of graphs a etworks.. Ma results We start here by statg the two ma results of ths work.
3 Theorem.. Let be the ajacecy matrx of a coecte graph G. The the followg cotos are equvalet: (a) G s walk-regular; (b) (c) () k ; k has a costat agoal for atural umbers e has costat agoal e has costat agoal for ; S G, l. (e) The walk etropy Theorem.. Let be the ajacecy matrx of a graph G. The oe of the followg cotos hols: S (a) G s walk-regular. The G, l for every (b) G s a regular but ot walk-regular graph. The Moreover, lm S G, l lm S G (c) There s some ;, such that S G, l for every. S G, l for every. 3. Proof of the Theorem We start by seeg that (a) clearly mples (b). For (b) mples (a), let T p T p p T be the characterstc polyomal of the graph G. The Cayley-Hamlto theorem yels If k has a costat agoal for atural umbers p p m m m has a costat agoal. k m a m, the p. 3
4 Clearly, (a) mples () whch s equvalet to (c). We shall prove that () mples (b). We follow the techques use for Theorem. []. For, we coser Tre e to be a real aalytc fucto. s power seres k! 3! 4! usg that G has o loops a fucto 3 4 k 3 a the lmt k k k s the egree of the oe Coser the aalytc lm s epeet of the oe, showg that G s regular. Repeatg the argumet we get successvely that k 3,4. k s epeet of the oe for () mples (e): let y be the costat value of the etres of e. The Z y a S y y G, l l. y y (e) mples (a): follows from Theorem.. Q.E.D. 4. uxlary eftos a results Before statg the proof of the Theorem. we ee to trouce some eftos a auxlary results, whch are gve below. We rem the reaer that gve a set X x x of real umbers, the varace s efe as,, s 4
5 X EX EX s s x x. s s Defto 4.: Gve a matrx M wth agoal etres the agoal varace as M,,M, ot all zero, we trouce M M,, M. M Let us ow state a proof the followg auxlary result. Proposto 4.: Let be the ajacecy matrx of a coecte graph G. The oe of the followg cotos hols: (a) e has costat agoal (b) e has o costat agoal etres a G s a regular graph. The e a lm e ; for (c) There s some such that e for every. Proof: We stgush the followg mutually exclug cases accorg to Theorem : () G s walk-regular, equvaletly, () e has ot costat agoal, for ay e has costat agoal.. The e for. Observe that for lm e e lm Z we have a e, where the (Perro) egevector of correspog to the maxmal egevalue. I that stuato e e. Z lm : : Therefore lm e s equvalet to beg costat, or G beg regular. s 5
6 If G s ot regular the the aalytc fucto e Clearly, there s some such that e for for every. Q.E.D. a lm e. We cotue ow wth some other auxlary results ee to prove the Theorem. Let be the egevalues of, such that etres y y y have,, of j j e we efe a vector z y y y. For the vector of agoal l l,,l of real umbers. We z ze y l y wth z l y l et e, where the equalty s a rect applcato of Haamar s theorem for the postve efte matrx Grgesoh [] states that Theorem 4.3. Let c,3, 4 a c e / 5 The [], e. The remarkable result of Borwe a a let z be efe as before. c z z ze. Remarks 4.5. (a) Observe that a pror t s ot eve clear that the sum z ze s postve. (b) Borwe-Grgesoh equalty mproves a prevous bou gve by Kostat a Mchor []. 5. Proof of the Theorem We kow that S G, l for every. Observe that for Z Tr e a the vertex etropy s y y S G Z y y Z z e z, l l l l Z Z Z Z 6
7 The Borwe-Grgersoh [] equalty yels c S G Z z Z, l Moreover, the arthmetc mea-geometrc mea equalty yels / / Tr Z Tr e y e e We stgush two stuatos at : () z, that s y for,,. The, Z Tr e y a therefore S G, l Z l. Z I partcular, for ay, the arthmetc-geometrc mea equalty yels / / Tr Z Tr e e e e whch mples that all e have the same value, that s that all have the same value. Tr, we have that for,,. The, the graph G s empty (t has o Sce lks) a S G, l for ay. () z. The there s a fferetable fucto c such that S G, l Z z l. Z 7
8 Sce Z there s a fferetable fucto e satsfyg e such that e. S G, l z such For every M, usg the compactess of the terval, M, there exsts a M that e for, M S G, l.. Moreover, recall from [3] that Ths lmt s l except whe there s a commo value c,,. The latter property mples that G s a regular graph. We coser these cases separately. (3) ssume that G s ot a regular graph. The such that for, we have S G, l. Therefore there exsts a e z. S G, l. that s, (4) ssume G s a regular graph. We may assume that G s ot walk-regular. The, accorg wth the aalyss [3], the maxmal value lm S G, l lm S G,. Q.E.D. I closg, the maxmum of the walk etropy at for the walk-regular graphs. Ths meas that, walk-regularty graphs. Refereces: S G, l s ot attae for ay Moreover,,.e., S G, l, s attae oly S G ca be use as a varat to characterze 8
9 [] M. Bez, ote o walk etropes graphs, Lear lgebra ppl. 445 (4) [] J. Borwe, R. Grgesoh, class of expoetal equaltes (Preprt). [3] J.. e la Peña, I. Gutma, J. Raa, Estmatg the Estraa ex, Lear lgebra ppl. 47 (7) [4] H. Deg, S. Raekovć, I. Gutma, The Estraa ex. pplcatos of Graph Spectra, Math. Ist., Belgrae, (9) 3-4. [5] E. Estraa, The Structure of Complex Networks. Theory a pplcatos, Oxfor Uversty Press, UK,. [6] E. Estraa, J.. e la Peña, N. Hatao, Walk etropes graphs, Lear lgebra ppl. 443 (4) [7] E. Estraa, J.. Roríguez-elázquez, Subgraph cetralty complex etworks, Phys. Rev. E 7 (5) [8] E. Estraa,, N. Hatao, M. Bez, The physcs of commucablty complex etworks, Phys. Rep. 54 () [9] I. Gutma, H. Deg, S. Raekovć, The Estraa ex: a upate survey. Selecte Topcs o pplcatos of Graph Spectra, Math. Ist., Beogra, () [] B. Kostat, P. W. Mchor, The geeralze Cayley map from a algebrac group to ts Le algebra, I The orbt metho geometry a physcs, pp Brkhäuser Bosto, 3. 9
(2014) ISSN
Estraa, Eresto a e la Pea, Jose too (4) Maxmum walk etropy mples walk regularty. Lear lgebra a ts pplcatos, 458. pp. 54-547. ISSN 4-3795, http://x.o.org/.6/j.laa.4.6.3 Ths verso s avalable at https://strathprts.strath.ac.uk/5879/
More informationX 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 informationMATH 247/Winter Notes on the adjoint and on normal operators.
MATH 47/Wter 00 Notes o the adjot ad o ormal operators I these otes, V s a fte dmesoal er product space over, wth gve er * product uv, T, S, T, are lear operators o V U, W are subspaces of V Whe we say
More informationChapter 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 informationChapter 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 informationSolutions to Odd-Numbered End-of-Chapter Exercises: Chapter 17
Itroucto to Ecoometrcs (3 r Upate Eto) by James H. Stock a Mark W. Watso Solutos to O-Numbere E-of-Chapter Exercses: Chapter 7 (Ths erso August 7, 04) 05 Pearso Eucato, Ic. Stock/Watso - Itroucto to Ecoometrcs
More informationBounds for the Connective Eccentric Index
It. J. Cotemp. Math. Sceces, Vol. 7, 0, o. 44, 6-66 Bouds for the Coectve Eccetrc Idex Nlaja De Departmet of Basc Scece, Humates ad Socal Scece (Mathematcs Calcutta Isttute of Egeerg ad Maagemet Kolkata,
More informationC.11 Bang-bang Control
Itroucto to Cotrol heory Iclug Optmal Cotrol Nguye a e -.5 C. Bag-bag Cotrol. Itroucto hs chapter eals wth the cotrol wth restrctos: s boue a mght well be possble to have scotutes. o llustrate some of
More informationStrong 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 informationThe 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 informationTHE 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 informationMultivariate 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 informationON THE CHROMATIC NUMBER OF GENERALIZED STABLE KNESER GRAPHS
ON THE CHROMATIC NUMBER OF GENERALIZED STABLE KNESER GRAPHS JAKOB JONSSON Abstract. For each teger trple (, k, s) such that k 2, s 2, a ks, efe a graph the followg maer. The vertex set cossts of all k-subsets
More information02/15/04 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 informationNon-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 informationAbout 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 informationHamilton s principle for non-holonomic systems
Das Hamltosche Przp be chtholoome Systeme, Math. A. (935), pp. 94-97. Hamlto s prcple for o-holoomc systems by Georg Hamel Berl Traslate by: D. H. Delphech I the paper Le prcpe e Hamlto et l holoomsme,
More informationThe 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 informationρ < 1 be five real numbers. The
Lecture o BST 63: Statstcal Theory I Ku Zhag, /0/006 Revew for the prevous lecture Deftos: covarace, correlato Examples: How to calculate covarace ad correlato Theorems: propertes of correlato ad covarace
More informationChapter 4 Multiple Random Variables
Revew for the prevous lecture: Theorems ad Examples: How to obta the pmf (pdf) of U = g (, Y) ad V = g (, Y) Chapter 4 Multple Radom Varables Chapter 44 Herarchcal Models ad Mxture Dstrbutos Examples:
More informationMaps on Triangular Matrix Algebras
Maps o ragular Matrx lgebras HMED RMZI SOUROUR Departmet of Mathematcs ad Statstcs Uversty of Vctora Vctora, BC V8W 3P4 CND sourour@mathuvcca bstract We surveys results about somorphsms, Jorda somorphsms,
More informationChapter 3. Differentiation 3.3 Differentiation Rules
3.3 Dfferetato Rules 1 Capter 3. Dfferetato 3.3 Dfferetato Rules Dervatve of a Costat Fucto. If f as te costat value f(x) = c, te f x = [c] = 0. x Proof. From te efto: f (x) f(x + ) f(x) o c c 0 = 0. QED
More informationComplete 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 informationCIS 800/002 The Algorithmic Foundations of Data Privacy October 13, Lecture 9. Database Update Algorithms: Multiplicative Weights
CIS 800/002 The Algorthmc Foudatos of Data Prvacy October 13, 2011 Lecturer: Aaro Roth Lecture 9 Scrbe: Aaro Roth Database Update Algorthms: Multplcatve Weghts We ll recall aga) some deftos from last tme:
More informationLINEARLY CONSTRAINED MINIMIZATION BY USING NEWTON S METHOD
Jural Karya Asl Loreka Ahl Matematk Vol 8 o 205 Page 084-088 Jural Karya Asl Loreka Ahl Matematk LIEARLY COSTRAIED MIIMIZATIO BY USIG EWTO S METHOD Yosza B Dasrl, a Ismal B Moh 2 Faculty Electrocs a Computer
More informationM2S1 - EXERCISES 8: SOLUTIONS
MS - EXERCISES 8: SOLUTIONS. As X,..., X P ossoλ, a gve that T ˉX, the usg elemetary propertes of expectatos, we have E ft [T E fx [X λ λ, so that T s a ubase estmator of λ. T X X X Furthermore X X X From
More informationResearch 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 informationCOV. Violation of constant variance of ε i s but they are still independent. The error term (ε) is said to be heteroscedastic.
c Pogsa Porchawseskul, Faculty of Ecoomcs, Chulalogkor Uversty olato of costat varace of s but they are stll depedet. C,, he error term s sad to be heteroscedastc. c Pogsa Porchawseskul, Faculty of Ecoomcs,
More informationThird 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= 2. Statistic - function that doesn't depend on any of the known parameters; examples:
of Samplg Theory amples - uemploymet househol cosumpto survey Raom sample - set of rv's... ; 's have ot strbuto [ ] f f s vector of parameters e.g. Statstc - fucto that oes't epe o ay of the ow parameters;
More informationPacking of graphs with small product of sizes
Joural of Combatoral Theory, Seres B 98 (008) 4 45 www.elsever.com/locate/jctb Note Packg of graphs wth small product of szes Alexadr V. Kostochka a,b,,gexyu c, a Departmet of Mathematcs, Uversty of Illos,
More informationChapter 3. Differentiation 3.2 Differentiation Rules for Polynomials, Exponentials, Products and Quotients
3.2 Dfferetato Rules 1 Capter 3. Dfferetato 3.2 Dfferetato Rules for Polyomals, Expoetals, Proucts a Quotets Rule 1. Dervatve of a Costat Fucto. If f as te costat value f(x) = c, te f x = [c] = 0. x Proof.
More informationTESTS BASED ON MAXIMUM LIKELIHOOD
ESE 5 Toy E. Smth. The Basc Example. TESTS BASED ON MAXIMUM LIKELIHOOD To llustrate the propertes of maxmum lkelhood estmates ad tests, we cosder the smplest possble case of estmatg the mea of the ormal
More informationLecture 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 informationGraphs and graph models-graph terminology and special types of graphs-representing graphs and graph isomorphism -connectivity-euler and Hamilton
Prepare by Dr. A.R.VIJAYALAKSHMI Graphs a graph moels-graph termology a specal types of graphs-represetg graphs a graph somorphsm -coectty-euler a Hamlto paths Graph Graph: A graph G = (V, E) cossts of
More informationMA 524 Homework 6 Solutions
MA 524 Homework 6 Solutos. Sce S(, s the umber of ways to partto [] to k oempty blocks, ad c(, s the umber of ways to partto to k oempty blocks ad also the arrage each block to a cycle, we must have S(,
More informationGeneralized Linear Regression with Regularization
Geeralze Lear Regresso wth Regularzato Zoya Bylsk March 3, 05 BASIC REGRESSION PROBLEM Note: I the followg otes I wll make explct what s a vector a what s a scalar usg vec t or otato, to avo cofuso betwee
More informationExtend 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 informationDr. Shalabh. Indian Institute of Technology Kanpur
Aalyss of Varace ad Desg of Expermets-I MODULE -I LECTURE - SOME RESULTS ON LINEAR ALGEBRA, MATRIX THEORY AND DISTRIBUTIONS Dr. Shalabh Departmet t of Mathematcs t ad Statstcs t t Ida Isttute of Techology
More informationAN UPPER BOUND FOR THE PERMANENT VERSUS DETERMINANT PROBLEM BRUNO GRENET
AN UPPER BOUND FOR THE PERMANENT VERSUS DETERMINANT PROBLEM BRUNO GRENET Abstract. The Permaet versus Determat problem s the followg: Gve a matrx X of determates over a feld of characterstc dfferet from
More information. 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 informationJohns Hopkins University Department of Biostatistics Math Review for Introductory Courses
Johs Hopks Uverst Departmet of Bostatstcs Math Revew for Itroductor Courses Ratoale Bostatstcs courses wll rel o some fudametal mathematcal relatoshps, fuctos ad otato. The purpose of ths Math Revew s
More information1 Convergence of the Arnoldi method for eigenvalue problems
Lecture otes umercal lear algebra Arold method covergece Covergece of the Arold method for egevalue problems Recall that, uless t breaks dow, k steps of the Arold method geerates a orthogoal bass of a
More informationCS286.2 Lecture 4: Dinur s Proof of the PCP Theorem
CS86. Lecture 4: Dur s Proof of the PCP Theorem Scrbe: Thom Bohdaowcz Prevously, we have prove a weak verso of the PCP theorem: NP PCP 1,1/ (r = poly, q = O(1)). Wth ths result we have the desred costat
More information9 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 informationJohns Hopkins University Department of Biostatistics Math Review for Introductory Courses
Johs Hopks Uverst Departmet of Bostatstcs Math Revew for Itroductor Courses Ratoale Bostatstcs courses wll rel o some fudametal mathematcal relatoshps, fuctos ad otato. The purpose of ths Math Revew s
More information5 Short Proofs of Simplified Stirling s Approximation
5 Short Proofs of Smplfed Strlg s Approxmato Ofr Gorodetsky, drtymaths.wordpress.com Jue, 20 0 Itroducto Strlg s approxmato s the followg (somewhat surprsg) approxmato of the factoral,, usg elemetary fuctos:
More informationA nonsmooth Levenberg-Marquardt method for generalized complementarity problem
ISSN 746-7659 Egla UK Joural of Iformato a Computg Scece Vol. 7 No. 4 0 pp. 67-7 A osmooth Leveberg-Marquart metho for geeralze complemetarty problem Shou-qag Du College of Mathematcs Qgao Uversty Qgao
More informationChapter 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 informationCesaro Supermodular Order and Archimedean Copulas
Joural of Sceces, Islamc Republc of Ira 6(): 7-76 (05) Uversty of Tehra, ISSN 06-04 http://jsceces.ut.ac.r Cesaro Supermoular Orer a Archmeea Copulas H.R. Nl Sa *, M. Am, M. Khajar, a N. Salm Departmet
More informationChapter 4 Multiple Random Variables
Revew o BST 63: Statstcal Theory I Ku Zhag, /0/008 Revew for Chapter 4-5 Notes: Although all deftos ad theorems troduced our lectures ad ths ote are mportat ad you should be famlar wth, but I put those
More informationmeans the first term, a2 means the term, etc. Infinite Sequences: follow the same pattern forever.
9.4 Sequeces ad Seres Pre Calculus 9.4 SEQUENCES AND SERIES Learg Targets:. Wrte the terms of a explctly defed sequece.. Wrte the terms of a recursvely defed sequece. 3. Determe whether a sequece s arthmetc,
More informationPROJECTION 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 informationExercises for Square-Congruence Modulo n ver 11
Exercses for Square-Cogruece Modulo ver Let ad ab,.. Mark True or False. a. 3S 30 b. 3S 90 c. 3S 3 d. 3S 4 e. 4S f. 5S g. 0S 55 h. 8S 57. 9S 58 j. S 76 k. 6S 304 l. 47S 5347. Fd the equvalece classes duced
More informationThe Topological Indices of some Dendrimer Graphs
Iraa J Math Chem 8 March 7 5 5 Iraa Joral of Mathematcal Chemstry Joral homepage: wwwjmckashaacr The Topologcal Ices of some Dermer Graphs M R DARASHEH a M NAMDARI b AND S SHOKROLAHI b a School of Mathematcs
More informationF. Inequalities. HKAL Pure Mathematics. 進佳數學團隊 Dr. Herbert Lam 林康榮博士. [Solution] Example Basic properties
進佳數學團隊 Dr. Herbert Lam 林康榮博士 HKAL Pure Mathematcs F. Ieualtes. Basc propertes Theorem Let a, b, c be real umbers. () If a b ad b c, the a c. () If a b ad c 0, the ac bc, but f a b ad c 0, the ac bc. Theorem
More informationUNIT 7 RANK CORRELATION
UNIT 7 RANK CORRELATION Rak Correlato Structure 7. Itroucto Objectves 7. Cocept of Rak Correlato 7.3 Dervato of Rak Correlato Coeffcet Formula 7.4 Te or Repeate Raks 7.5 Cocurret Devato 7.6 Summar 7.7
More informationEconometric 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 informationChapter 3 Sampling For Proportions and Percentages
Chapter 3 Samplg For Proportos ad Percetages I may stuatos, the characterstc uder study o whch the observatos are collected are qualtatve ature For example, the resposes of customers may marketg surveys
More informationDouble 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( ) = ( ) ( ) Chapter 13 Asymptotic Theory and Stochastic Regressors. Stochastic regressors model
Chapter 3 Asmptotc Theor ad Stochastc Regressors The ature of eplaator varable s assumed to be o-stochastc or fed repeated samples a regresso aalss Such a assumpto s approprate for those epermets whch
More informationDr. Shalabh Department of Mathematics and Statistics Indian Institute of Technology Kanpur
Aalyss of Varace ad Desg of Exermets-I MODULE II LECTURE - GENERAL LINEAR HYPOTHESIS AND ANALYSIS OF VARIANCE Dr Shalabh Deartmet of Mathematcs ad Statstcs Ida Isttute of Techology Kaur Tukey s rocedure
More informationis said to be conditionally commuting if f and g commute on a nonempty subset of the set of coincidence points
6 Vol 03, Issue03; Sep-Dec 01 PUBLICATIONS OF PROBLEMS & APPLICATION IN ENGINEERING RESEARCH - PAPER http://jpaper.com/ ISSN: 30-8547; e-issn: 30-8555 Commo Fxe Pots for Par of Cotoally Commutg a Asorg
More informationA 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 informationX X X E[ ] E X E X. is the ()m n where the ( i,)th. j element is the mean of the ( i,)th., then
Secto 5 Vectors of Radom Varables Whe workg wth several radom varables,,..., to arrage them vector form x, t s ofte coveet We ca the make use of matrx algebra to help us orgaze ad mapulate large umbers
More informationEVALUATION OF FUNCTIONAL INTEGRALS BY MEANS OF A SERIES AND THE METHOD OF BOREL TRANSFORM
EVALUATION OF FUNCTIONAL INTEGRALS BY MEANS OF A SERIES AND THE METHOD OF BOREL TRANSFORM Jose Javer Garca Moreta Ph. D research studet at the UPV/EHU (Uversty of Basque coutry) Departmet of Theoretcal
More informationLINEAR RECURRENT SEQUENCES AND POWERS OF A SQUARE MATRIX
INTEGERS: ELECTRONIC JOURNAL OF COMBINATORIAL NUMBER THEORY 6 2006, #A12 LINEAR RECURRENT SEQUENCES AND POWERS OF A SQUARE MATRIX Hacèe Belbachr 1 USTHB, Departmet of Mathematcs, POBox 32 El Ala, 16111,
More informationOn the construction of symmetric nonnegative matrix with prescribed Ritz values
Joural of Lear ad Topologcal Algebra Vol. 3, No., 14, 61-66 O the costructo of symmetrc oegatve matrx wth prescrbed Rtz values A. M. Nazar a, E. Afshar b a Departmet of Mathematcs, Arak Uversty, P.O. Box
More informationOn 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 informationJournal 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 informationQ-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 informationA 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 informationEntropies & Information Theory
Etropes & Iformato Theory LECTURE II Nlajaa Datta Uversty of Cambrdge,U.K. See lecture otes o: http://www.q.damtp.cam.ac.uk/ode/223 quatum system States (of a physcal system): Hlbert space (fte-dmesoal)
More informationLebesgue 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 informationUNIT 6 CORRELATION COEFFICIENT
UNIT CORRELATION COEFFICIENT Correlato Coeffcet Structure. Itroucto Objectves. Cocept a Defto of Correlato.3 Tpes of Correlato.4 Scatter Dagram.5 Coeffcet of Correlato Assumptos for Correlato Coeffcet.
More informationh-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 informationPart 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 informationLower Bounds of the Kirchhoff and Degree Kirchhoff Indices
SCIENTIFIC PUBLICATIONS OF THE STATE UNIVERSITY OF NOVI PAZAR SER. A: APPL. MATH. INFORM. AND MECH. vol. 7, (205), 25-3. Lower Bouds of the Krchhoff ad Degree Krchhoff Idces I. Ž. Mlovaovć, E. I. Mlovaovć,
More informationSeveral Trigonometric Hamming Similarity Measures of Rough Neutrosophic Sets and their Applications in Decision Making
New Tres Neutrosophc Theory a pplcatos KLYN MONDL 1 URPTI PRMNIK 2* FLORENTIN MRNDCHE 3 1 Departmet of Mathematcs Jaavpur Uversty West egal Ia Emal:kalyamathematc@gmalcom ² Departmet of Mathematcs Naalal
More informationAssignment 7/MATH 247/Winter, 2010 Due: Friday, March 19. Powers of a square matrix
Assgmet 7/MATH 47/Wter, 00 Due: Frday, March 9 Powers o a square matrx Gve a square matrx A, ts powers A or large, or eve arbtrary, teger expoets ca be calculated by dagoalzg A -- that s possble (!) Namely,
More informationhp 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 informationPoint 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 informationMu 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 informationNumerical Analysis Formulae Booklet
Numercal Aalyss Formulae Booklet. Iteratve Scemes for Systems of Lear Algebrac Equatos:.... Taylor Seres... 3. Fte Dfferece Approxmatos... 3 4. Egevalues ad Egevectors of Matrces.... 3 5. Vector ad Matrx
More informationSimple Linear Regression
Statstcal Methods I (EST 75) Page 139 Smple Lear Regresso Smple regresso applcatos are used to ft a model descrbg a lear relatoshp betwee two varables. The aspects of least squares regresso ad correlato
More informationarxiv:math/ v2 [math.gr] 26 Feb 2001
arxv:math/0101070v2 [math.gr] 26 Feb 2001 O drft ad etropy growth for radom walks o groups Aa Erschler (Dyuba) e-mal: aad@math.tau.ac.l, erschler@pdm.ras.ru 1 Itroducto prelmary verso We cosder symmetrc
More informationMaximum Likelihood Estimation
Marquette Uverst Maxmum Lkelhood Estmato Dael B. Rowe, Ph.D. Professor Departmet of Mathematcs, Statstcs, ad Computer Scece Coprght 08 b Marquette Uverst Maxmum Lkelhood Estmato We have bee sag that ~
More informationExam FM Formula Summary Version no driver 11/14/2006
Exam FM Formula Summary Verso 2.01 o rver 11/14/2006 Itroucto Sce ASM oes ot have a formula summary, I ece to comple oe to use as I starte workg o ol test questos. I the terest of other actuaral stuets,
More informationInternational Journal of Systems Science. Almost Decouplability of any Directed Weighted Network Topology
Almost Decouplablty of ay Drecte Weghte etwork Topology Joural: Mauscrpt ID: TSYS-0-0 Mauscrpt Type: Orgal Paper Date Submtte by the Author: -Aug-0 Complete Lst of Authors: Ca, g; orthwest Uversty for
More informationAnalysis of a Repairable (n-1)-out-of-n: G System with Failure and Repair Times Arbitrarily Distributed
Amerca Joural of Mathematcs ad Statstcs. ; (: -8 DOI:.593/j.ajms.. Aalyss of a Reparable (--out-of-: G System wth Falure ad Repar Tmes Arbtrarly Dstrbuted M. Gherda, M. Boushaba, Departmet of Mathematcs,
More informationArithmetic Mean and Geometric Mean
Acta Mathematca Ntresa Vol, No, p 43 48 ISSN 453-6083 Arthmetc Mea ad Geometrc Mea Mare Varga a * Peter Mchalča b a Departmet of Mathematcs, Faculty of Natural Sceces, Costate the Phlosopher Uversty Ntra,
More informationSpecial 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 informationCHAPTER 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 information18.413: Error Correcting Codes Lab March 2, Lecture 8
18.413: Error Correctg Codes Lab March 2, 2004 Lecturer: Dael A. Spelma Lecture 8 8.1 Vector Spaces A set C {0, 1} s a vector space f for x all C ad y C, x + y C, where we take addto to be compoet wse
More informationDIFFERENTIAL GEOMETRIC APPROACH TO HAMILTONIAN MECHANICS
DIFFERENTIAL GEOMETRIC APPROACH TO HAMILTONIAN MECHANICS Course Project: Classcal Mechacs (PHY 40) Suja Dabholkar (Y430) Sul Yeshwath (Y444). Itroducto Hamltoa mechacs s geometry phase space. It deals
More informationMarcinkiewicz strong laws for linear statistics of ρ -mixing sequences of random variables
Aas da Academa Braslera de Cêcas 2006 784: 65-62 Aals of the Brazla Academy of Sceces ISSN 000-3765 www.scelo.br/aabc Marckewcz strog laws for lear statstcs of ρ -mxg sequeces of radom varables GUANG-HUI
More informationSummary 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 informationA 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 informationLecture 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 informationCHAPTER 4 RADICAL EXPRESSIONS
6 CHAPTER RADICAL EXPRESSIONS. The th Root of a Real Number A real umber a s called the th root of a real umber b f Thus, for example: s a square root of sce. s also a square root of sce ( ). s a cube
More information