Research on the Industrial Geographic Concentration and Regional Specialization in China

Size: px
Start display at page:

Download "Research on the Industrial Geographic Concentration and Regional Specialization in China"

Transcription

1 Advaces Socal Scece, Educato ad Humates Research, volume 85 4th Iteratoal Coferece o Maagemet Scece, Educato Techology, Arts, Socal Scece ad Ecoomcs (MSETASSE 2016) Research o the Idustral Geographc Cocetrato ad Regoal Specalzato Cha We Chao1 Ca Ax2 Su Yafe3 1. Departmet of Face, Guagdog Uversty of Scece ad Techology, Doggua , Cha; 23. School of Ecoomcs ad Maagemet, Cha Uversty of Geosceces (Wuha), Wuha , Cha Keywords: Idustral Cocetrato, Specalzato, Idustral Structure; Abstract: The dustral dvso of labor ad geographcal cocetrato s the key factor to affect ad determe the dustral layout ad dustral optmzato of Cha. Collectg 2014 Chese dustres the provcal spatal data dstrbuto, to study Cha's dustral geography cocetrato ad the degree of regoal specalzato, ad for the Chese optmzato of dustral layout ad promote dustral developmet to provde polcy recommedatos. Itroducto The measuremet of dustral geographc cocetrato ad regoal specalzato s a basc theme the emprcal aalyss of regoal ecoomy. Idustral geographc cocetrato s the measuremet that dustry the dstrbuto of the geographcal elemets of the mbalace. The more ueve spatal dstrbuto of a dustry, whch meas a large share of the dustry are cocetrated a few areas, the hgher the degree of geographcal cocetrato. Regoal specalzato s a measure of the ueve dstrbuto of regoal ecoomc actvtes dfferet dustres. The proporto of each dustry's total ecoomc actvty a rego s a bg dfferece, whch meas that all ecoomc actvtes the rego focus o a small umber of dustres, the rego's professoal level s hgher. I fact, the ubalaced of the dustral geographc cocetrato ad spatal dstrbuto s the two sdes of a co. Therefore, t s geerally used to measure the spatal dstrbuto of the dcators to measure the dustral geographc cocetrato, such as the G coeffcet, etc.. As far as the spatal dstrbuto of dustry s ot balaced, t reflects the proporto of each spatal ut a certa dustry. Accordg to the uderstadg of the expectatos of dfferet levels, there are two cases amed "absolute geographcal cocetrato" ad "relatve geographcal cocetrato". "Absolute geographcal cocetrato" that the proporto of the space ut s ot dfferet from the expected level. If there s N space ut, the N ut s expected to be the level of 1/. I fact ths s ot approprate, the total ecoomc sze of each rego s dfferet, so t s expected that they ca accommodate a certa dfferece the dustry share. Assumg 10% for the total ecoomc scale Zhejag accouted for the proporto of the total sze of the ecoomy, of course, we expect ts textle dustry accouted for the etre textle dustry (.e. all the provces of the textle dustry ad the proporto for 10%); f 1% total ecoomc scale Tbet accouted for the proporto of the total sze of the ecoomy. We of course hope ts textle dustry accouted for the proporto of the textle dustry as a whole s oly 1%. So from the relatve sese, Zhejag the textle dustry accouted for 10% of Tbet the textle dustry accouted for Copyrght 2016, the Authors. Publshed by Atlats Press. Ths s a ope access artcle uder the CC BY-NC lcese ( 1626

2 Advaces Socal Scece, Educato ad Humates Research, volume 85 more tha 1% of ts expected value, so the two s o dfferece. But the absolute sese, there are sgfcat dffereces betwee the two, may come to the cocluso that the textle dustry Zhejag has cocetrated. Ths s because the absolute sese that Zhejag ad Tbet the expected proporto s 1 / 31 ( 31 provces, Hog Kog, Macao ad Tawa excluded), ad Zhejag the textle dustry accouted for 10% hgher tha the level of expectato, ad Tbet the textle dustry accouted for more tha 1% less tha the level of hope. I cosderato of ths, ths artcle wll use the relatve geographcal cocetrato method to measure the degree of Cha's dustral geographc cocetrato, order to elmate the dfferece caused by the ecoomc gap betwee the provces of the absolute geographc cocetrato. Materals ad Methods G coeffcet s commoly used to measure the data dstrbuto dversty dex, the value of area surrouded by Lorez curve ad the 45 degree le ad the sosceles rght agled tragle area rato, value betwee 0 ad 1, ts value that bgger data dfferece s bgger, ts value s more smaller to show smaller dffereces the data. G Coeffcet Locato s o the bass of the G coeffcet, addg spatal dstrbuto characterstcs, the measure of ecoomc actvty the geographcal space dstrbuto s ot balaced degree. Its formula s: 1 G = 2 x x j (a) 2 x =1 j =1 x = I formula (a), whe xj for the orgal data, or whe X X k (that s x = cr, at ths crk 1 X X / x = x= cr, Z for ), for the absolute G coeffcet. At that tme x = tme, that s Z / Z each geographcal ut of all ecoomc actvtes of the scale dex, for the relatve coeffcet of G. The relatve G coeffcet cotrols the overall sze of the geographcal ut, ad s qute reasoable. The value of Gee coeffcet rages from 0 to (1-1/), the hgher the value of the value, the hgher the degree of cocetrato. Results Accordg to the relatve locato of the G coeffcet of the calculato formula to calculate the cocetrato of Cha's dustry, the results show fgure 1: 1627

3 Advaces Socal Scece, Educato ad Humates Research, volume 85 Fgure 1 Cha dustral cocetrato relatve G coeffcet hstogram From Fgure 1 ca be foud, The G coeffcet of metal products dustry relatve s mmum(0.2797). Back tur s food maufacturg(0.3042), chemcal materals ad chemcal products maufacturg dustry(0.3099), beverage maufacturg dustry(0.3142), prtg ad record medum copy(0.3188). Vsble geeral lfe ad lght dustral goods dustry cocetrato s relatvely low, the spatal dstrbuto of the relatve equlbrum, show that Chese provces of ther ow provce lght dustry supply relatve equlbrum ca be bascally acheve self-suffcecy. The relatve G coeffcet of waste of resources ad waste materals back of the processg dustry s hghest(0.7262), followed by statoery ad sports goods maufacturg(0.6963), wood processg, bamboo, cae, palm, ad straw products dustry(0.6664), leather ad fur, feather ad related products maufacturg(0.6633), petroleum processg ad cokg ad uclear fuel processg(0.6101). I geeral, the dustral cocetrato of hgh tech maufacturg dustry s relatvely hgh, ad ts spatal dstrbuto s relatvely cocetrated. O the oe had, the reaso s due to certa areas of resource costrats, o the other had s due to techcal lmtatos or early accumulato of sustaable effects ad dstace. Leads to the degree of dustral cocetrato further mproved, for the resources edowmet ad lead to dustry dffereces betwee terveto effect s ot sgfcat. However, the state ca crease supply ad ad for educato, techology ad the developmet of dustry more balaced. Dscusso The measuremet of regoal specalzato level ad the dex of dustral geographc cocetrato have certa smlarty, whch are to measured data dfferet uts. The dfferece betwee them les the fact that the data s dfferet from the overall ut of data. I the dustral geographc cocetrato measuremet, the overall data for all ecoomc actvty a dustral scale, segmetato overall ut of the data for the total area of each sub rego; the measuremet of regoal specalzato, the overall data for all ecoomc actvty a sub regoal scale, 1628

4 Advaces Socal Scece, Educato ad Humates Research, volume 85 segmetato ut of the overall data costtute the major dustry of all ecoomc actvty the sub rego. Because of the computg dustry geographc cocetrato dex ad calculatg the local specalzato dex are the same prcple. Therefore, used to calculate the dustral geographc cocetrato dex accordg to type(a) accordg to the classfcato of area calculato the relatve balace of the dustry level, ca be used to calculatg the level of regoal specalzato. By usg the relatve Gee coeffcet, the degree of specalzato Cha s measured, ad the results are show Fgure 2. Fgure 2 Cha regoal specalzato relatve Gee coeffcet radar chart From Fgure 2 ca be foud, the Tbet Regoal Specalzato relatve G coeffcet of the hghest (0.8607) ad subsequetly tur s Gasu (0.7391), Qgha (0.7109), Yua (0.6565), Xjag (0.6307) that dustral structure these regos the mbalace, whch wll serously affected the coordated developmet of the area, also the root causes of the area has log lagged behd other regos. Istead, Jagsu's regoal specalzato relatve G coeffcet s mmum (0.2686) ad subsequetly tur s Shadog (0.2782), Taj (0.2980), Hea (0.3213), Ahu (0.3253) that these areas of the dustral structure to balace, the dustry the regoal allocato of reasoably uform dstrbuto, whch wll also these areas the future developmet lay a sold foudato, so the future have more favorable codtos for the developmet of. Therefore, Cha should pay more atteto to for the remote ad backward areas of dustry support, from the captal, techology, polcy, persoel ad educato gve a certa tlt, help the balaced allocato of dustres whle developg the dustry's ow reproducto ad developmet ablty, thus fudametally help them out of poverty ad rch, harmoous developmet. 1629

5 Advaces Socal Scece, Educato ad Humates Research, volume 85 Coclusos For of above Cha Idustral geographc cocetrato ad problems exstg the regoal specalzato, t s recommeded to speed up the trasformato ad upgradg of tradtoal dustres; to promote the healthy developmet of strategc emergg dustres ad advaced maufacturg dustry; promote the servce dustry especally the developmet of moder servce dustry ad growth; reasoable layout of frastructure facltes ad basc dustres; developmet of moder formato techology dustral system, promote the coordated developmet of medum ad small mcro eterprse; balaced cofgurato of the dustry the rego; the regoal dustral portfolo optmzato, promote dustral upgradg; focus o support backward areas behd the dustry, accelerate the ovato the upgradg of the dustry's ablty to drve. Refereces [1] Cafe, Pa Feghua. Geographcal cocetrato of dustres, dustral agglomerato ad dustral cluster: Measuremet ad detfcato [J]. Progress geography, 2007,02:1-13. [2] Wag Yeqag, We We. Idustral characterstcs, spatal competto ad geographc cocetrato of maufacturg dustry: Emprcal Evdece from Cha [J]. maagemet world, 2007,04: [3] Lu Chuxa. Research o the measuremet method of dustral geographc cocetrato [J]. ecoomc geography, 2006,05: [4] Yua Yua Weg, Gao Rux. Rao Weju. Regoal specalzato ad geographc cocetrato of dustres of comparatve study [J]. Research o ecoomcs ad maagemet, 2009,04: [5] Goofy. Theoretcal aalyss ad applcato of dustral geographc cocetrato [J]. Najg socal scece, 2002,01: Itroduce Chao We(1984-), male, Ha atoalty, Wuha Hube, Lecturer, Departmet of Face, Guagdog Uversty Of Scece Ad Techology, doctoral studets, School of Ecoomcs ad Maagemet, Cha Uversty Of Geosceces wuha. The ma research drecto s the coordated developmet of Hgher Educato Ax Ca(1993-), female, Ha atoalty, Hegshu Hebe, postgraduate, School of Ecoomcs ad Maagemet, Cha Uversty Of Geosceces wuha. Research drecto s regoal ecoomy. Yafe Su(1993-), male, Ha atoalty, Yogcheg Hebe, postgraduate, School of Ecoomcs ad Maagemet, Cha Uversty Of Geosceces wuha. Research drecto s regoal ecoomy. 1630

Research on SVM Prediction Model Based on Chaos Theory

Research on SVM Prediction Model Based on Chaos Theory Advaced Scece ad Techology Letters Vol.3 (SoftTech 06, pp.59-63 http://dx.do.org/0.457/astl.06.3.3 Research o SVM Predcto Model Based o Chaos Theory Sog Lagog, Wu Hux, Zhag Zezhog 3, College of Iformato

More information

Evaluation on Ecological Environment of Scientific and Technological Innovation Talents in China

Evaluation on Ecological Environment of Scientific and Technological Innovation Talents in China AMSE JOURNALS-2016-Seres: Modellg C; Vol. 77; N 1; pp 108-118 Submtted July 2016; Revsed Oct. 15, 2016, Accepted Dec. 10, 2016 Evaluato o Ecologcal Evromet of Scetfc ad Techologcal Iovato Talets Cha Nabg

More information

Journal of Chemical and Pharmaceutical Research, 2014, 6(7): Research Article

Journal of Chemical and Pharmaceutical Research, 2014, 6(7): Research Article Avalable ole www.jocpr.com Joural of Chemcal ad Pharmaceutcal Research, 04, 6(7):4-47 Research Artcle ISSN : 0975-7384 CODEN(USA) : JCPRC5 Predcto of CNG automoble owershp by usg the combed model Ku Huag,

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

Summary of the lecture in Biostatistics

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

More information

Block-Based Compact Thermal Modeling of Semiconductor Integrated Circuits

Block-Based Compact Thermal Modeling of Semiconductor Integrated Circuits Block-Based Compact hermal Modelg of Semcoductor Itegrated Crcuts Master s hess Defese Caddate: Jg Ba Commttee Members: Dr. Mg-Cheg Cheg Dr. Daqg Hou Dr. Robert Schllg July 27, 2009 Outle Itroducto Backgroud

More information

Bootstrap Method for Testing of Equality of Several Coefficients of Variation

Bootstrap Method for Testing of Equality of Several Coefficients of Variation Cloud Publcatos Iteratoal Joural of Advaced Mathematcs ad Statstcs Volume, pp. -6, Artcle ID Sc- Research Artcle Ope Access Bootstrap Method for Testg of Equalty of Several Coeffcets of Varato Dr. Navee

More information

Dynamic Analysis of Coupling Relationship between Economic Development and Ecological Environment of Hubei Province

Dynamic Analysis of Coupling Relationship between Economic Development and Ecological Environment of Hubei Province Iteratoal Joural of Busess, Humates ad Techology Vol. 5, No. 2 Arl 2015 Dyamc Aalyss of Coulg Relatosh betwee Ecoomc Develomet ad Ecologcal Evromet of Hube Provce Luo Jua Lecturer College of Mathematcs

More information

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

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

More information

Fuzzy Comprehensive Evaluation of Research on China s Sports Industry Development in Leisure Era

Fuzzy Comprehensive Evaluation of Research on China s Sports Industry Development in Leisure Era Sed Orders for Reprts to reprts@bethamscece.ae 67 The Ope Cyberetcs & Systemcs Joral, 05, 9, 67-676 Ope Access Fzzy Comprehesve Evalato of Research o Cha s Sports Idstry Developmet Lesre Era Zhyog X Departmet

More information

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

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

More information

Chapter 8. Inferences about More Than Two Population Central Values

Chapter 8. Inferences about More Than Two Population Central Values Chapter 8. Ifereces about More Tha Two Populato Cetral Values Case tudy: Effect of Tmg of the Treatmet of Port-We tas wth Lasers ) To vestgate whether treatmet at a youg age would yeld better results tha

More information

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

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

More information

Optimization Research of Batch Order Processing Queue in Internet Consumption Custom Marketing

Optimization Research of Batch Order Processing Queue in Internet Consumption Custom Marketing Jot Iteratoal Socal Scece, Educato, Laguage, Maagemet ad Busess Coferece (JISEM 205 Optmzato Research of Batch Order Processg Queue Iteret Cosumpto Custom Maretg Ru Wag, a, Jao Tag2,b* ad Ye Yag3,c, 2,

More information

= 1. UCLA STAT 13 Introduction to Statistical Methods for the Life and Health Sciences. Parameters and Statistics. Measures of Centrality

= 1. UCLA STAT 13 Introduction to Statistical Methods for the Life and Health Sciences. Parameters and Statistics. Measures of Centrality UCLA STAT Itroducto to Statstcal Methods for the Lfe ad Health Sceces Istructor: Ivo Dov, Asst. Prof. of Statstcs ad Neurology Teachg Assstats: Fred Phoa, Krste Johso, Mg Zheg & Matlda Hseh Uversty of

More information

Population Distribution Evolution Characteristics and Shift Growth Analysis in Shiyang River Basin

Population Distribution Evolution Characteristics and Shift Growth Analysis in Shiyang River Basin Iteratoal Joural of Geosceces, 204, 5, 395-403 Publshed Ole October 204 ScRes. http://www.scrp.org/joural/jg http://dx.do.org/0.4236/jg.204.53 Populato Dstrbuto Evoluto Characterstcs ad Shft Growth Aalyss

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

Journal of Chemical and Pharmaceutical Research, 2014, 6(7): Research Article

Journal of Chemical and Pharmaceutical Research, 2014, 6(7): Research Article Avalable ole www.jocpr.com Joural of Chemcal ad Pharmaceutcal Research, 2014, 6(7):1035-1041 Research Artcle ISSN : 0975-7384 CODEN(SA) : JCPRC5 Desg ad developmet of kowledge maagemet platform for SMEs

More information

Multiple Choice Test. Chapter Adequacy of Models for Regression

Multiple Choice Test. Chapter Adequacy of Models for Regression Multple Choce Test Chapter 06.0 Adequac of Models for Regresso. For a lear regresso model to be cosdered adequate, the percetage of scaled resduals that eed to be the rage [-,] s greater tha or equal to

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

Lecture 9: Tolerant Testing

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

More information

Measures of Dispersion

Measures of Dispersion Chapter 8 Measures of Dsperso Defto of Measures of Dsperso (page 31) A measure of dsperso s a descrptve summary measure that helps us characterze the data set terms of how vared the observatos are from

More information

Empirical study on pharmaceutical economic and investment in research and development based on correlation analysis

Empirical study on pharmaceutical economic and investment in research and development based on correlation analysis Avalable ole www.jocpr.com Joural of Chemcal ad Pharmaceutcal Research, 24, 6(4):67-674 Research Artcle ISSN : 975-7384 CODEN(USA) : JCPRC5 Emprcal study o pharmaceutcal ecoomc ad vestmet research ad developmet

More information

Reliability evaluation of distribution network based on improved non. sequential Monte Carlo method

Reliability evaluation of distribution network based on improved non. sequential Monte Carlo method 3rd Iteratoal Coferece o Mecatrocs, Robotcs ad Automato (ICMRA 205) Relablty evaluato of dstrbuto etwork based o mproved o sequetal Mote Carlo metod Je Zu, a, Cao L, b, Aog Tag, c Scool of Automato, Wua

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

Mean is only appropriate for interval or ratio scales, not ordinal or nominal.

Mean is only appropriate for interval or ratio scales, not ordinal or nominal. Mea Same as ordary average Sum all the data values ad dvde by the sample sze. x = ( x + x +... + x Usg summato otato, we wrte ths as x = x = x = = ) x Mea s oly approprate for terval or rato scales, ot

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

SPATIAL RAINFALL FIELD SIMULATION WITH RANDOM CASCADE INTRODUCING OROGRAPHIC EFFECTS ON RAINFAL

SPATIAL RAINFALL FIELD SIMULATION WITH RANDOM CASCADE INTRODUCING OROGRAPHIC EFFECTS ON RAINFAL Proc. of the d Asa Pacfc Assocato of Hydrology ad Water Resources (APHW) Coferece, July 5-8, 4, Sutec Sgapore Iteratoal Coveto Exhbto Cetre, Sgapore, vol., pp. 67-64, 4 SPATIAL RAINFALL FIELD SIMULATION

More information

Study on a Fire Detection System Based on Support Vector Machine

Study on a Fire Detection System Based on Support Vector Machine Sesors & Trasducers, Vol. 8, Issue, November 04, pp. 57-6 Sesors & Trasducers 04 by IFSA Publshg, S. L. http://www.sesorsportal.com Study o a Fre Detecto System Based o Support Vector Mache Ye Xaotg, Wu

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

We have already referred to a certain reaction, which takes place at high temperature after rich combustion.

We have already referred to a certain reaction, which takes place at high temperature after rich combustion. ME 41 Day 13 Topcs Chemcal Equlbrum - Theory Chemcal Equlbrum Example #1 Equlbrum Costats Chemcal Equlbrum Example #2 Chemcal Equlbrum of Hot Bured Gas 1. Chemcal Equlbrum We have already referred to a

More information

Lecture 1 Review of Fundamental Statistical Concepts

Lecture 1 Review of Fundamental Statistical Concepts Lecture Revew of Fudametal Statstcal Cocepts Measures of Cetral Tedecy ad Dsperso A word about otato for ths class: Idvduals a populato are desgated, where the dex rages from to N, ad N s the total umber

More information

Solid State Device Fundamentals

Solid State Device Fundamentals Sold State Devce Fudametals 9 polar jucto trasstor Sold State Devce Fudametals 9. polar Jucto Trasstor NS 345 Lecture ourse by Alexader M. Zatsev alexader.zatsev@cs.cuy.edu Tel: 718 98 81 4N101b Departmet

More information

Chapter 13, Part A Analysis of Variance and Experimental Design. Introduction to Analysis of Variance. Introduction to Analysis of Variance

Chapter 13, Part A Analysis of Variance and Experimental Design. Introduction to Analysis of Variance. Introduction to Analysis of Variance Chapter, Part A Aalyss of Varace ad Epermetal Desg Itroducto to Aalyss of Varace Aalyss of Varace: Testg for the Equalty of Populato Meas Multple Comparso Procedures Itroducto to Aalyss of Varace Aalyss

More information

A Study of the Reproducibility of Measurements with HUR Leg Extension/Curl Research Line

A Study of the Reproducibility of Measurements with HUR Leg Extension/Curl Research Line HUR Techcal Report 000--9 verso.05 / Frak Borg (borgbros@ett.f) A Study of the Reproducblty of Measuremets wth HUR Leg Eteso/Curl Research Le A mportat property of measuremets s that the results should

More information

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

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

More information

MEASURES OF DISPERSION

MEASURES OF DISPERSION MEASURES OF DISPERSION Measure of Cetral Tedecy: Measures of Cetral Tedecy ad Dsperso ) Mathematcal Average: a) Arthmetc mea (A.M.) b) Geometrc mea (G.M.) c) Harmoc mea (H.M.) ) Averages of Posto: a) Meda

More information

Module 1 : The equation of continuity. Lecture 5: Conservation of Mass for each species. & Fick s Law

Module 1 : The equation of continuity. Lecture 5: Conservation of Mass for each species. & Fick s Law Module : The equato of cotuty Lecture 5: Coservato of Mass for each speces & Fck s Law NPTEL, IIT Kharagpur, Prof. Sakat Chakraborty, Departmet of Chemcal Egeerg 2 Basc Deftos I Mass Trasfer, we usually

More information

Third handout: On the Gini Index

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

More information

Multiple Regression. More than 2 variables! Grade on Final. Multiple Regression 11/21/2012. Exam 2 Grades. Exam 2 Re-grades

Multiple Regression. More than 2 variables! Grade on Final. Multiple Regression 11/21/2012. Exam 2 Grades. Exam 2 Re-grades STAT 101 Dr. Kar Lock Morga 11/20/12 Exam 2 Grades Multple Regresso SECTIONS 9.2, 10.1, 10.2 Multple explaatory varables (10.1) Parttog varablty R 2, ANOVA (9.2) Codtos resdual plot (10.2) Trasformatos

More information

Lesson 3. Group and individual indexes. Design and Data Analysis in Psychology I English group (A) School of Psychology Dpt. Experimental Psychology

Lesson 3. Group and individual indexes. Design and Data Analysis in Psychology I English group (A) School of Psychology Dpt. Experimental Psychology 17/03/015 School of Psychology Dpt. Expermetal Psychology Desg ad Data Aalyss Psychology I Eglsh group (A) Salvador Chacó Moscoso Susaa Saduvete Chaves Mlagrosa Sáchez Martí Lesso 3 Group ad dvdual dexes

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

i 2 σ ) i = 1,2,...,n , and = 3.01 = 4.01

i 2 σ ) i = 1,2,...,n , and = 3.01 = 4.01 ECO 745, Homework 6 Le Cabrera. Assume that the followg data come from the lear model: ε ε ~ N, σ,,..., -6. -.5 7. 6.9 -. -. -.9. -..6.4.. -.6 -.7.7 Fd the mamum lkelhood estmates of,, ad σ ε s.6. 4. ε

More information

Convergence of the Desroziers scheme and its relation to the lag innovation diagnostic

Convergence of the Desroziers scheme and its relation to the lag innovation diagnostic Covergece of the Desrozers scheme ad ts relato to the lag ovato dagostc chard Méard Evromet Caada, Ar Qualty esearch Dvso World Weather Ope Scece Coferece Motreal, August 9, 04 o t t O x x x y x y Oservato

More information

(Monte Carlo) Resampling Technique in Validity Testing and Reliability Testing

(Monte Carlo) Resampling Technique in Validity Testing and Reliability Testing Iteratoal Joural of Computer Applcatos (0975 8887) (Mote Carlo) Resamplg Techque Valdty Testg ad Relablty Testg Ad Setawa Departmet of Mathematcs, Faculty of Scece ad Mathematcs, Satya Wacaa Chrsta Uversty

More information

is the score of the 1 st student, x

is the score of the 1 st student, x 8 Chapter Collectg, Dsplayg, ad Aalyzg your Data. Descrptve Statstcs Sectos explaed how to choose a sample, how to collect ad orgaze data from the sample, ad how to dsplay your data. I ths secto, you wll

More information

Outline. Point Pattern Analysis Part I. Revisit IRP/CSR

Outline. Point Pattern Analysis Part I. Revisit IRP/CSR Pot Patter Aalyss Part I Outle Revst IRP/CSR, frst- ad secod order effects What s pot patter aalyss (PPA)? Desty-based pot patter measures Dstace-based pot patter measures Revst IRP/CSR Equal probablty:

More information

On the Link Between the Concepts of Kurtosis and Bipolarization. Abstract

On the Link Between the Concepts of Kurtosis and Bipolarization. Abstract O the Lk etwee the Cocepts of Kurtoss ad polarzato Jacques SILE ar-ila Uversty Joseph Deutsch ar-ila Uversty Metal Haoka ar-ila Uversty h.d. studet) Abstract I a paper o the measuremet of the flatess of

More information

Analysis of Lagrange Interpolation Formula

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

More information

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

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

More information

Quantitative analysis requires : sound knowledge of chemistry : possibility of interferences WHY do we need to use STATISTICS in Anal. Chem.?

Quantitative analysis requires : sound knowledge of chemistry : possibility of interferences WHY do we need to use STATISTICS in Anal. Chem.? Ch 4. Statstcs 4.1 Quattatve aalyss requres : soud kowledge of chemstry : possblty of terfereces WHY do we eed to use STATISTICS Aal. Chem.? ucertaty ests. wll we accept ucertaty always? f ot, from how

More information

Lecture 2 - What are component and system reliability and how it can be improved?

Lecture 2 - What are component and system reliability and how it can be improved? Lecture 2 - What are compoet ad system relablty ad how t ca be mproved? Relablty s a measure of the qualty of the product over the log ru. The cocept of relablty s a exteded tme perod over whch the expected

More information

Handout #1. Title: Foundations of Econometrics. POPULATION vs. SAMPLE

Handout #1. Title: Foundations of Econometrics. POPULATION vs. SAMPLE Hadout #1 Ttle: Foudatos of Ecoometrcs Course: Eco 367 Fall/015 Istructor: Dr. I-Mg Chu POPULATION vs. SAMPLE From the Bureau of Labor web ste (http://www.bls.gov), we ca fd the uemploymet rate for each

More information

DATE: 21 September, 1999 TO: Jim Russell FROM: Peter Tkacik RE: Analysis of wide ply tube winding as compared to Konva Kore CC: Larry McMillan

DATE: 21 September, 1999 TO: Jim Russell FROM: Peter Tkacik RE: Analysis of wide ply tube winding as compared to Konva Kore CC: Larry McMillan M E M O R A N D U M DATE: 1 September, 1999 TO: Jm Russell FROM: Peter Tkack RE: Aalyss of wde ply tube wdg as compared to Kova Kore CC: Larry McMlla The goal of ths report s to aalyze the spral tube wdg

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

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

Notes on the proof of direct sum for linear subspace

Notes on the proof of direct sum for linear subspace Notes o the proof of drect sum for lear subspace Da u, Qa Guo, Huzhou Xag, B uo, Zhoghua Ta, Jgbo Xa* College of scece, Huazhog Agrcultural Uversty, Wuha, Hube, Cha * Correspodece should be addressed to

More information

Optimality Conditions for Distributive Justice

Optimality Conditions for Distributive Justice Optmalty Codtos for Dstrbutve Justce Joh Hooker Carege Mello Uversty Aprl 2008 1 Just Dstrbuto The problem: How to dstrbute resources Tax breaks Medcal care Salares Educato Govermet beefts 2 Justce ad

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

CENTRE FOR ECONOMIC RESEARCH WORKING PAPER SERIES

CENTRE FOR ECONOMIC RESEARCH WORKING PAPER SERIES CENTRE FOR ECONOMIC RESEARCH WORKING PAPER SERIES 2001 Mmum Wages for Roald McDoald Moopsoes: A Theory of Moopsostc Competto by V Bhaskar ad Ted To A Commet Frak Walsh, Uversty College Dubl WP01/18 September

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

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

Section l h l Stem=Tens. 8l Leaf=Ones. 8h l 03. 9h 58

Section l h l Stem=Tens. 8l Leaf=Ones. 8h l 03. 9h 58 Secto.. 6l 34 6h 667899 7l 44 7h Stem=Tes 8l 344 Leaf=Oes 8h 5557899 9l 3 9h 58 Ths dsplay brgs out the gap the data: There are o scores the hgh 7's. 6. a. beams cylders 9 5 8 88533 6 6 98877643 7 488

More information

Combining Gray Relational Analysis with Cumulative Prospect Theory for Multi-sensor Target Recognition

Combining Gray Relational Analysis with Cumulative Prospect Theory for Multi-sensor Target Recognition Sesors & Trasducers, Vol 172, Issue 6, Jue 2014, pp 39-44 Sesors & Trasducers 2014 by IFSA Publshg, S L http://wwwsesorsportalcom Combg Gray Relatoal Aalyss wth Cumulatve Prospect Theory for Mult-sesor

More information

Consistency test of martial arts competition evaluation criteria based on mathematical ahp model

Consistency test of martial arts competition evaluation criteria based on mathematical ahp model ISSN : 0974-7435 Volume 8 Issue 2 BoTechology BoTechology A Ida Joural Cosstecy test of martal arts competto evaluato crtera based o mathematcal ahp model Hu Wag Isttute of Physcal Educato, JagSu Normal

More information

Centroids & Moments of Inertia of Beam Sections

Centroids & Moments of Inertia of Beam Sections RCH 614 Note Set 8 S017ab Cetrods & Momets of erta of Beam Sectos Notato: b C d d d Fz h c Jo L O Q Q = ame for area = ame for a (base) wdth = desgato for chael secto = ame for cetrod = calculus smbol

More information

Generating Multivariate Nonnormal Distribution Random Numbers Based on Copula Function

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

More information

Objectives of Multiple Regression

Objectives of Multiple Regression Obectves of Multple Regresso Establsh the lear equato that best predcts values of a depedet varable Y usg more tha oe eplaator varable from a large set of potetal predctors {,,... k }. Fd that subset of

More information

Application of Improved Grey Correlative Method in Safety Evaluation on Fully Mechanized Mining Faces

Application of Improved Grey Correlative Method in Safety Evaluation on Fully Mechanized Mining Faces Avalable ole at www.scecedrect.com Proceda Earth ad Plaetary Scece 2 ( 2011 ) 58 63 The Secod Iteratoal Coferece o Mg Egeerg ad Metallurgcal Techology Applcato of Improved Grey Correlatve Method Safety

More information

Median as a Weighted Arithmetic Mean of All Sample Observations

Median as a Weighted Arithmetic Mean of All Sample Observations Meda as a Weghted Arthmetc Mea of All Sample Observatos SK Mshra Dept. of Ecoomcs NEHU, Shllog (Ida). Itroducto: Iumerably may textbooks Statstcs explctly meto that oe of the weakesses (or propertes) of

More information

Economic drivers. Input and output prices Adjustment under ITQs

Economic drivers. Input and output prices Adjustment under ITQs Ecoomc drvers Iput ad output prces Adjustmet uder ITQs Outle Questo beg examed How are fshers lely to adjust ther fshg operatos uder ITQs? Methodologes to loo at the ssue Cost fuctos Proft fuctos Case

More information

Risk management of hazardous material transportation

Risk management of hazardous material transportation Maagemet of atural Resources, Sustaable Developmet ad Ecologcal azards 393 Rs maagemet of hazardous materal trasportato J. Auguts, E. Uspuras & V. Matuzas Lthuaa Eergy Isttute, Lthuaa Abstract I recet

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

Fourth Order Four-Stage Diagonally Implicit Runge-Kutta Method for Linear Ordinary Differential Equations ABSTRACT INTRODUCTION

Fourth Order Four-Stage Diagonally Implicit Runge-Kutta Method for Linear Ordinary Differential Equations ABSTRACT INTRODUCTION Malasa Joural of Mathematcal Sceces (): 95-05 (00) Fourth Order Four-Stage Dagoall Implct Ruge-Kutta Method for Lear Ordar Dfferetal Equatos Nur Izzat Che Jawas, Fudzah Ismal, Mohamed Sulema, 3 Azm Jaafar

More information

desa is the smallest administrative unit in Indonesia, which corresponds to shuraku in Japan

desa is the smallest administrative unit in Indonesia, which corresponds to shuraku in Japan Lad Use Chage Patter Jakarta Suburb: The Case of Bekas Dstrct Itroducto The kowledge o how fast the urbazato process s ad how t relates to ts determats wll cotrbute to how the lad use plaer could make

More information

best estimate (mean) for X uncertainty or error in the measurement (systematic, random or statistical) best

best estimate (mean) for X uncertainty or error in the measurement (systematic, random or statistical) best Error Aalyss Preamble Wheever a measuremet s made, the result followg from that measuremet s always subject to ucertaty The ucertaty ca be reduced by makg several measuremets of the same quatty or by mprovg

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

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

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

More information

Chapter 11 The Analysis of Variance

Chapter 11 The Analysis of Variance Chapter The Aalyss of Varace. Oe Factor Aalyss of Varace. Radomzed Bloc Desgs (ot for ths course) NIPRL . Oe Factor Aalyss of Varace.. Oe Factor Layouts (/4) Suppose that a expermeter s terested populatos

More information

An Introduction to. Support Vector Machine

An Introduction to. Support Vector Machine A Itroducto to Support Vector Mache Support Vector Mache (SVM) A classfer derved from statstcal learg theory by Vapk, et al. 99 SVM became famous whe, usg mages as put, t gave accuracy comparable to eural-etwork

More information

Permutation Tests for More Than Two Samples

Permutation Tests for More Than Two Samples Permutato Tests for ore Tha Two Samples Ferry Butar Butar, Ph.D. Abstract A F statstc s a classcal test for the aalyss of varace where the uderlyg dstrbuto s a ormal. For uspecfed dstrbutos, the permutato

More information

VOL. 5, NO. 8, August 2015 ISSN ARPN Journal of Science and Technology All rights reserved.

VOL. 5, NO. 8, August 2015 ISSN ARPN Journal of Science and Technology All rights reserved. Applcato of SVM Model the Evaluato of the SMEs echologcal Iovato Capablt Xao-L Wag Assoc. Prof., School of Ecoomcs & Maagemet, Zhogua Uverst of echolog, Zhegzhou, Cha sx mdwxl@sa.com ABSRAC Applg the SVM

More information

Simple Linear Regression

Simple 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 information

Principal-subordinate hierarchical multi-objective programming model of initial water rights allocation

Principal-subordinate hierarchical multi-objective programming model of initial water rights allocation Water Scece ad Egeerg, 2009, 2(2): 05-6 do:0.3882/j.ss.674-2370.2009.02.02 http://b.hhu.edu.c e-mal: wse@hhu.edu.c Prcpal-subordate herarchcal mult-objectve programmg model of tal water rghts allocato

More information

The Turning Point of Macroeconomics?

The Turning Point of Macroeconomics? ETH Zürch Ivtato for Macro-Ecoophyscs 30, November 200 Hrosh Yoshkawa Uversty of Tokyo The Turg Pot of Macroecoomcs? The 2008-09 Facal Crss (2005=00 30 20 Exports 0 00 IdustralProducto 90 80 70 60 2006

More information

ENGI 3423 Simple Linear Regression Page 12-01

ENGI 3423 Simple Linear Regression Page 12-01 ENGI 343 mple Lear Regresso Page - mple Lear Regresso ometmes a expermet s set up where the expermeter has cotrol over the values of oe or more varables X ad measures the resultg values of aother varable

More information

Department of Agricultural Economics. PhD Qualifier Examination. August 2011

Department of Agricultural Economics. PhD Qualifier Examination. August 2011 Departmet of Agrcultural Ecoomcs PhD Qualfer Examato August 0 Istructos: The exam cossts of sx questos You must aswer all questos If you eed a assumpto to complete a questo, state the assumpto clearly

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

Chapter Statistics Background of Regression Analysis

Chapter Statistics Background of Regression Analysis Chapter 06.0 Statstcs Backgroud of Regresso Aalyss After readg ths chapter, you should be able to:. revew the statstcs backgroud eeded for learg regresso, ad. kow a bref hstory of regresso. Revew of Statstcal

More information

1. BLAST (Karlin Altschul) Statistics

1. BLAST (Karlin Altschul) Statistics Parwse seuece algmet global ad local Multple seuece algmet Substtuto matrces Database searchg global local BLAST Seuece statstcs Evolutoary tree recostructo Gee Fdg Prote structure predcto RNA structure

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

Periodic Table of Elements. EE105 - Spring 2007 Microelectronic Devices and Circuits. The Diamond Structure. Electronic Properties of Silicon

Periodic Table of Elements. EE105 - Spring 2007 Microelectronic Devices and Circuits. The Diamond Structure. Electronic Properties of Silicon EE105 - Srg 007 Mcroelectroc Devces ad Crcuts Perodc Table of Elemets Lecture Semcoductor Bascs Electroc Proertes of Slco Slco s Grou IV (atomc umber 14) Atom electroc structure: 1s s 6 3s 3 Crystal electroc

More information

SPECIAL CONSIDERATIONS FOR VOLUMETRIC Z-TEST FOR PROPORTIONS

SPECIAL CONSIDERATIONS FOR VOLUMETRIC Z-TEST FOR PROPORTIONS SPECIAL CONSIDERAIONS FOR VOLUMERIC Z-ES FOR PROPORIONS Oe s stctve reacto to the questo of whether two percetages are sgfcatly dfferet from each other s to treat them as f they were proportos whch the

More information

Unsupervised Learning and Other Neural Networks

Unsupervised Learning and Other Neural Networks CSE 53 Soft Computg NOT PART OF THE FINAL Usupervsed Learg ad Other Neural Networs Itroducto Mture Destes ad Idetfablty ML Estmates Applcato to Normal Mtures Other Neural Networs Itroducto Prevously, all

More information

Bounds on the expected entropy and KL-divergence of sampled multinomial distributions. Brandon C. Roy

Bounds on the expected entropy and KL-divergence of sampled multinomial distributions. Brandon C. Roy Bouds o the expected etropy ad KL-dvergece of sampled multomal dstrbutos Brado C. Roy bcroy@meda.mt.edu Orgal: May 18, 2011 Revsed: Jue 6, 2011 Abstract Iformato theoretc quattes calculated from a sampled

More information

1 Onto functions and bijections Applications to Counting

1 Onto functions and bijections Applications to Counting 1 Oto fuctos ad bectos Applcatos to Coutg Now we move o to a ew topc. Defto 1.1 (Surecto. A fucto f : A B s sad to be surectve or oto f for each b B there s some a A so that f(a B. What are examples of

More information

ESS Line Fitting

ESS Line Fitting ESS 5 014 17. Le Fttg A very commo problem data aalyss s lookg for relatoshpetwee dfferet parameters ad fttg les or surfaces to data. The smplest example s fttg a straght le ad we wll dscuss that here

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

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

Finite Difference Approximations for Fractional Reaction-Diffusion Equations and the Application In PM2.5

Finite Difference Approximations for Fractional Reaction-Diffusion Equations and the Application In PM2.5 Iteratoal Symposum o Eergy Scece ad Chemcal Egeerg (ISESCE 5) Fte Dfferece Appromatos for Fractoal Reacto-Dffuso Equatos ad the Applcato I PM5 Chagpg Xe, a, Lag L,b, Zhogzha Huag,c, Jya L,d, PegLag L,e

More information