List of Books on Statistics

List of Books on Statistics (Available in the Library) Library Indian Institute of Technology Gandhinagar . Sr. No. Bibliography 1. Acevedo, M. F. (20...

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List of Books on

Statistics (Available in the Library)

Library Indian Institute of Technology Gandhinagar

Sr. No.

Bibliography

1.

Acevedo, M. F. (2013). Data analysis and statistics for geography, environmental science, and engineering. Boca Raton: CRC Press. 519.5 ACE 020004

2.

Agresti, A. (2009). Statistical methods for the social sciences. New Delhi: Pearson Education. 519.5024301 AGR 004848

3.

Alefeld, G. (1983). Introduction to interval computations. New York: Academic Press. 519.4 ALE 003003

4.

Allen, E. (2007). Modeling with to stochastic differential equations. Dordrecht: Springer. 519.2 ALL 014586

5.

Allen, L. J. S. (2011). Introduction to stochastic processes with applications to biology. Boca Raton: CRC Press. 519.23 ALL 017103

6.

Allison, P. D. (2009). Fixed effects regression models. London: Sage Publications. 519.536 ALL 007727

7.

Alvo, M. (2014). Statistical methods for ranking data. New York: Springer. 519.5 ALV 021836

8.

Anderson, D. R. (2001). Statistics for business and economics. New Delhi: Cengage Learning. 519.5 AND 002531

9.

Applebaum, D. (2004). Levy processes and stochastic calculus. Cambridge: Cambridge University Press. 519.22 APP 004286

10.

Arnold, B. C. (2008). First course in order statistics. Philadelphia: Society for Industrial and Applied Mathematics (SIAM). 519.5 ARN 014124

11.

Ash, R. B. (2000). Probability and measure theory. London: Elsevier Academic Press. 519.2 ASH 003071

12.

Ash, R. B. (2008). Basic probability theory. New York: Dover Publication. 519.2 ASH 000808

13.

Asmussen, S. (2010). Stochastic simulation: algorithms and analysis. New York: Springer. 519.23 ASM 014590

14.

Athreya, K. B. (1972). Branching processes. New York: Springer-Verlag. 519.234 ATH 019374

15.

Athreya, K. B. (2006). Measure theory and probability theory. New York: Springer Science. 515.42 MEA 019378

16.

Athreya, K. B. (2006). Probability theory. New Delhi: Hindustan book agency. 519.2 ATH 020308

17.

Athreya, S. (2008). Measure & probability. Hyderabad: CRC Press. 519.2 ATH 010843

18.

Atkinson, K. E. (2004). Elementary numerical analysis. New Delhi: Wiley India. 519.4 ATK 003637

19.

Attard, P. (2002). Thermodynamics and statistical mechanics: equilibrium by entropy maximization. San Diego: Academic Press. 536.7 ATT 001129

20.

Attouch, H. (2002). Variational analysis in Sobolev and BV spaces: applications to PDEs and optimization. Philadelphia: Society for Industrial and Applied Mathematics (SIAM). 519.6 ATT 007514

21.

Aubin, J. P. (2007). Mathematical methods of game and economic theory. New York: Dover Publication. 519.3 AUB 004558

22.

Ayyub, B. M. (2003). Probability, statistics and reliability for engineers and scientists. New York: Champman and Hall. 519.502462 AYY 007702

23.

Ayyub, B. M. (2011). Probability, statistics, and reliability for engineers and scientists. Boca Raton: CRC Press. 519.502462 AYY 009794

24.

Azzalini, A. (2014). Skew-normal and related families. Cambridge: Cambridge University Press. 519.24 AZZ 019125

25.

Baase, S. (2000). Computer algorithms: introduction to design and analysis. New Delhi: Pearson Education. 519.7 BAA 005349

26.

Babu, R. (2010). Numerical methods. New Delhi: Pearson Education. 519.4 BAB 015816

27.

Baccelli, F. (2003). Elements of queueing theory: palm martingale calculus and stochastic recurrences. New York: Springer. 519.82 BAC 015586

28.

Bailey, N. T. J. (1995). Statistical methods in biology. Cambridge: Cambeidge University Press. 519.5024574 BAI 001916

29.

Baisnab, A. P. (1993). Elements of probability and statistics. New Delhi: Tata McGraw Hill Education. 519.2 BAI 005999

30.

Baltagi, B. H. (2002). Econometrics. New Delhi: Springer. 330.015195 BAL 003169

31.

Bansal, A. K. (2007). Bayesian parametric inference. New Delhi: Narosa Publishing House. 519.5 BAN 002674

32.

Barlow, R. J. (1989). Statistics: a guide to the use of statistical methods in the physical sciences. New York: Wiley India. 530.1595 BAR 018609

33.

Baron, M. (2007). Probability and statistics for computer scientists. Boca Raton: Chapman & Hall/CRC. 519.20113 BAR 009712

34.

Basilevsky, A. (1983). Applied matrix algebra in the statistical sciences. New York: Dover Publication. 519.5 BAS 004553

35.

Basu, A. (2011). Statistical inference: the minimum distance approach. Boca Raton: CRC Press. 519.544 BAS 013001

36.

Basu, A. K. (2003). Introduction to Stochastic Process. New Delhi: Narosa Publishing House. 519.82 BAS 002811

37.

Basu, A. K. (2010). Measure theory and probability. New Delhi: PHI Learning. 519.2 BAS 006668

38.

Bazaraa, M. S. (2006). Nonlinear programming: theory and algorithms. New Delhi: Wiley India. 519.76 BAZ 010307

39.

Belegundu, A. D. (2011). Optimization concepts and applications in engineering. New Delhi: Cambridge University Press. 519.602462 BEL 018166

40.

Bendat, J. S. (1993). Engineering applications of correlation and spectral analysis. New York: John Wiley & Sons. 519.53702462 BEN 012972

41.

Bhatia, R. (2012). Collected papers of S.R.S. Varadhan; vol. 2: PDE, SDE, diffusions, random media. New Delhi: Hindustan book agency. 519.2 BHA 020273

42.

Bhatia, R. (2012). Collected papers of S.R.S. Varadhan; vol.1: limit theorems, review articles. New Delhi: Hindustan book agency. 519.2 BHA 020272

43.

Bhatia, R. (2012). Collected papers of S.R.S. Varadhan; vol.3: large deviations. New Delhi: Hindustan book agency. 519.2 BHA 020274

44.

Bhatia, R. (2012). Collected papers of S.R.S. Varadhan; vol.4: particle systems and their large deviations. New Delhi: Hindustan book agency. 519.2 BHA 020275

45.

Biegler, L. T. (2010). Nonlinear programming: concepts, algorithms, and applications to chemical processes. Philadelphia: Society for Industrial and Applied Mathematics: Mathematical Programming Society. 519.76 BIE 008152

46.

Bierens, H. J. (2004). Introduction to the mathematical and statistical foundations of econometrics. [s.l]: Cambridge University Press. 330.015195 BIE 002608

47.

Billingsley, P. (2012). Probability and measure (3rd ed.). New Delhi: Wiley. 519.2 BIL 022017

48.

Binmore, K. (2007). Game theory: a very short introduction. New Delhi: Oxford University Press. 519.3 BIN 017514

49.

Birge, J. R. (2011). Introduction to stochastic programming. New York: Springer. 519.7 BIR 011452

50.

Bivand, R. S. (2013). Applied spatial data analysis with R (2nd ed.). New York: Springer Science. 519.5 BIV 021833

51.

Bloomfield, P. (2000). Fourier analysis of time series: an introduction. New York: Wiley. 519.55 BLO 014360

52.

Blunch, N. J. (2008). Introduction to structural equation modelling using SPSS and AMOS. New York: SAE International. 519.53502855369 BLU 007732

53.

Brandt, S. (1999). Data analysis: statistical and computational methods for Scientists and Engineers (3rd ed.). New York: Springer. 519.2 BRA 019228

54.

Breiman, L....[et al.]. (1998). Classification and regression trees. Boca Raton: Chapman and Hall/CRC Press. 519.536 BRE 017310

55.

Brian S. E. (2010). Handbook of statistical analyses using R. Boca Raton: CRC Press. 519.502855133 BRI 003837

56.

Bulmer, M. G. (1979). Principles of statistics. New York: Dover Publication. 519.5 BUL 004581

57.

Burden, R. L. (2001). Numerical analysis. New Delhi: Cengage Learning. 519.4 BUR 002432

58.

Calin, O. (2014). Geometric modeling in probability and statistics. New York: Springer. 519.5 CAL 020397

59.

Capinski, M. (2001). Probability through problems. New York: Springer-Verlag. 519.2076 CAP 007646

60.

Carmona, R. (1999). Stochastic partial differential equations: six perspectives. RI: American Mathematical Society. 519.2 CAR 013629

61.

Casella, G. (2002). Statistical inference. New Delhi: Cengage Learning. 519.5 CAS 002530

62.

Chalmers, D.J. (2009). O level statistics. Cambridge: Cambridge University Press. 519.5 CHA 002165

63.

Chambers, R. L. (2012). Introduction to model-based survey sampling with applications. Oxford: Oxford University Press. 519.52 CHA 014258

64.

Chandra, T. K. (1999). First course in asymptotic theory of statistics. New Delhi: Narosa Publishing House. 519.5 CHA 002631

65.

Chandra, T. K. (2001). First course in probability. New Delhi: Narosa Publishing House. 519 CHA 002630

66.

Chandrasekhar, S. (1989). Stochastic, statistical, and hydromagnetic problems in physics and astronomy. Chicago: University Of Chicago Press. 523.01 CHA 015548

67.

Chung, K. L. (1967). Markov chains with stationary transition probabilities. New York: Springer. 519.1 CHU 015591

68.

Chung, K. L. (2003). Elementary probability theory: with stochastic processes and an introduction to mathematical finance. . New York: Springer. 519.2 CHU 004594

69. 519.2 CIN

Probability and stochastics. New York: Springer. 014589

70.

Clarke, A. B. (1985). Probability and random processes: a first course with applications, (2nd ed.). New York: John Wiley & Sons. 519.1 CLA 021489

71.

Cooray, T. M. J. A. (2008). Applied time series: analysis and forecasting. New Delhi: Narosa Publishing House. 519.55 COO 002668

72.

Cowan, G. (1998). Statistical data analysis. New York: Oxford University Press. 519.5 COW 018549

73.

Cox, D. R. (2006). Principles of statistical inference. New York: Cambridge University Press. 519.54 COX 003119

74.

Cressie, N. A. C. (1993). Statistics for spatial data. New York: John Wiley & Sons. 519.535 CRE 021396

75.

Dalgaard, P. (2008). Introductory Statistics with R. New York: Springer. 519.50285 DAL 012368

76.

Das, N. G. (2009). Statistical methods. New Delhi: Tata McGraw Hill Education. 519.5 DAS 005782, 006015 and 005760

77.

Das Gupta, A. (2008). Asymptotic theory of statistics and probability. New York: Springer. 519.5 DAS 020698

78.

David (2009). Statistics. New Delhi: Viva Books. 300.151 DAV 004300

79.

Deb, K. (2010). Multi-objective optimization using evolutionary algorithms. New Delhi: Wiley India. 519.3 DEB 013382

80.

Efron, B. (1993). An introduction to the bootstrap. New York: Chapman & Hall. 519.544 EFR 009787

81.

Ethier, S. N. (2005). Markov processes: characterization and convergence. New York: Wiley Interscience. 519.233 ETH 021744

82.

Eubank, R. L. (2005). Kalman filter primer. Boca Raton: CRC Press. 519.23 EUB 019222

83.

Feldman, R. M. (2010). Applied probability and stochastic processes. New York: SpringerVerlag. 519.2 FEL 018290

84.

Field, A. (2009). Discovering statistics using SPSS. London: Sage Publications. 519.50285536 FIE 011731

85.

Field, A. (2013). Discovering statistics using IBM SPSS statistics (4th ed.). London: Sage Publications. 519.502855 FIE 018777

86.

Field, A. (2013). Discovering statistics using IBM SPSS statistics: and sex and drugs and rock and roll. London: Sage Publications. 519.50285536 FIE 017025

87.

Field, A. (2014). Discovering statistics using R. London: Sage Publications. 519.50285 FIE 018861

88.

Field, A. P. (2009). Discovering statistics using SPSS: and sex and drugs and rock n roll. Thousand oaks, calif.: Sage Publications. 519.50285536 FIE 011344

89.

Field, A. P. (2010). Discovering statistics using SAS: and sex and drugs and rock n roll. London: Sage Publications. 519.50285 FIE 007750

90.

Fishback, P. E. (2010). Linear and nonlinear programming with Maple: an interactive, applications-based approach. Boca Raton, FL: Chapman &Hall/CRC. 519.72 FIS 009791

91.

Forst, W. (2010). Optimization: theory and practice. New York: Springer. 519.6 FOR 010130

92.

Franke, J. (2008). Statistics of financial markets: an introduction. Berlin: Springer-Verlag. 332.015195 FRA 003552

93.

Fuller, W. A. (1996). Introduction to statistical time series. New York: Wiley. 519.55 FUL 014211

94.

Gallager, R. G. (2013). Stochastic processes: theory for applications. New York: Cambridge University Press. 519.23 GAL 018672

95.

Gardiner, C. (2009). Stochastic methods: a handbook for the natural and social sciences, (4th ed.). New York: Springer. 519.23 GAR 021472

96.

Gawarecki, L. (2011). Stochastic differential equations in infinite dimensions: with applications to stochastic partial differential equations. New York: Springer. 519.2 GAW 011674

97.

Gelman, A. (2006). Data analysis using regression and multilevel hierarchical models. New York: Cambridge University Press. 519.536 GEL 015013

98.

Gelman, A. (2014). Bayesian data analysis (3rd ed.). Boca Raton: CRC Press. 519.542 GEL 020692

99.

Goldberg, S. (1960). Probability: an introduction. New York: Dover Publication. 519.2 GOL 011033

100. Goodman, J. W. (2000). Statistical optics. New York: Wiley. 535.0727 GOO 013740 101. Goodman, R. (2006). Introduction to stochastic models. New York: Dover Publication. 519.2 GOO 004583 102. Gorroochurn, P. (2012). Classic problems of probability. New York: John Wiley & Sons. 519.2 GOR 016932 103. Goswami, A. (2006). Course in applied stochastic processes. New Delhi: Hindustan book agency. 519.2 GOS 020249 104. Gray, R. M. (2009). Probability, random processes, and ergodic properties (2nd ed.). New York: Springer. 519.2 GRA 021344 105. Grimmett, G. (2001). One thousand exercises in probability. New York: Oxford University Press. 519.2076 GRI 021810

106. Grimmett, G. R. (2001). Probability and random processes (3rd ed.). New York: Oxford University Press. 519.2 GRI 021342 and 021343 107. Gubner, J. A. (2006). Probability and random processes for electrical and computer engineers. Cambridge: Cambridge University Press. 519.2 GUB 021807 108. Gupta, S.C. (2002). Fundamentals of mathematical statistics. New Delhi: Sultan Chand. 519.2 GUP 000711 109. Haigh, J. (2012). Probability: a very short introduction. New Delhi: Oxford University Press. 519.2 HAI 017608 110. Hair, J. F. (2006). Multivariate data analysis. New Delhi: Pearson Education. 519.535 HAI 005061 111. Hajek, B. (2015). Random processes for engineers. Cambridge: Cambridge University Press. 519.23 HAJ 021607 112. Hamilton, J. D. (1994). Time series analysis. Princeton: Princeton University Press. 519.55 HAM 008011 113. Hamming, R. W. (1986). Numerical methods for scientists and engineers. New York: Dover Publication. 519.4 HAM 010083 114. Hanagal, D. D. (2009). Introduction to applied statistics: a non-calculus based approach. New Delhi: Narosa Publishing House. 519.5 HAN 002800 115. Hand, D. J. (2008). Statistics: a very short introduction. New Delhi: Oxford University Press. 519.5 HAN 017636 116. Hanneman, R. (2013). Basic statistics for social research. San Francisco: Jossey- Bass Inc Pub. 519.5 HAN 013181 117. Hilbe, J. M. (2009). Logistic regression models. Boca Raton: CRC Press. 519.536 HIL 003835 118. Hildebrand, F. B. (1987). Introduction to numerical analysis. New York: Dover Publication. 519.4 HIL 000759 119. Hill, T. (2006). Statistics: methods and applications: a comprehensive reference for science, industry, and data mining. Tulsa, Okla: StatSoft. 519.5024658 HIL 002091

120. H es W W… [et 519.2 HIN

]

3 Probability and statistics in engineering. New Delhi: Wiley. 003992

121. Hodges, J. L. (2005). Basic concepts of probability and statistics. Philadelphia: Society for Industrial and Applied Mathematics (SIAM). 519.2 HOD 014126 122. Hogg, R. V. (2005). Introduction to mathematical statistics. New Delhi: Pearson Education. 519.5 HOG 005047 123. Hogg, R. V. (2006). Probability and statistical inference. New Delhi: Pearson Education. 519.2 HOG 005071 124. Hojsgaard, S. (2012). Graphical models with R. New York: Springer. 519.535 HOJ 018656 125. Holden, H. (1996). Stochastic partial differential equations: a modeling, white noise functional approach. Boston: Birkhauser. 519.2 HOL 011419 126. Huber, P. J. (2009). Robust statistics. Hoboken, N.J.: John Wiley & Sons. 519.5 HUB 013367 127. Huber, P. J. (2011). Data analysis: what can be learned from the past 50 years. New Jersey: Wiley. 519.509 HUB 014210 128. Hughes, B. D. (1996). Random walks and random environments. New York: Oxford University Press. 530.159282 HUG 013080 129. Hurlbert, G. H. (2009). Linear optimization; The simplex workbook. New York: Springer. 519.92 HUR 008225 130. Husson, F. F. (2011). Exploratory multivariate analysis by example using R. Boca Raton: CRC Press. 519.535028551 HUS 017110 131. Hyvarinen, A. (2009). Natural image statistics: a probabilistic approach. New York: Springer. 006.37 HYV 018718 132. Infanger, G. (c201). Stochastic programming: the state of the art: in honor of George B. Dantzig. New York: Springer. 519.7 INF 011459

133. Iosifescu, M. (1980). Finite Markov processes and their applications. New York: Dover Publication. 519.23 IOS 000914 134. Isaacson, E. (1994). Analysis of numerical methods. New York: Dover Publication. 519.4 ISA 000760 135. Ito, K. (2008). Lagrange multiplier approach to variational problems and applications. Philadelphia: Society for Industrial and Applied Mathematics (SIAM). 519.3 ITO 004470 136. Ivezic, Z...[et al]. (2014). Statistics, data mining, and machine learning in astronomy: a practical python guide for the analysis of survey data. Princeton: Princeton University Press. 520.285631 IVE 017293 137. Jackman, S. (2009). Bayesian analysis for the social sciences. Chi Chester: Wiley. 519.542 JAC 014370 138. Jackson, E. (2003). Users guide to principal components. Canada: Jones & Bartlett Publishing. 519.5354 JAC 018655 139. Jacobs, K. (2010). Stochastic processes for physicists: understanding noisy systems. New York: Cambridge University Press. 519.2302453 JAC 013575 140. Jacod, J. (2003). Limit theorems for stochastic processes. Berlin: Springer-Verlag. 519.287 JAC 011443 141. Jahn, J. (2011). Vector optimization: theory, applications, and extensions. Berlin: SpringerVerlag. 519.7 JAH 011462 142. James, G. (2013). Introduction to statistical learning: with applications in R. New York: Springer. 519.5 JAM 020074 143. Jaynes, E. T. (2003). Probability theory the logic of science. Cambridge: Cambridge University Press. 519.2 JAY 017314 144. Jensen, F. V. (2007). Bayesian networks and decision graphs (2nd ed.). New York: Springer. 519.542 JEN 020658 145. Johnson, N. L. (1994). Continuous univariate distributions, v.1. Delhi: Wiley India. 519.24 JOH 001018

146. Johnson, N. L. (1997). Discrete multivariate distributions. New York: John Wiley. 519.24 JOH 001036 147. Johnson, R. A. (2009). Applied multivariate statistical analysis. New Delhi: PHI Learning. 519.535 JOH 006156 148. Jolliffe, I.T. (2002). Principal component analysis. New York: Springer. 519.535 JOL 018657 149. Jordan, M. I. (Ed.). (1999). Learning in graphical models. Cambridge: MIT Press. 519.5 JOR 021776 150. Joshi, M. C. (2004). Optimization: theory and practice. New Delhi: Narosa Publishing House. 519.7 JOS 002865 151. Jungnickel, D. (2005). Graphs, networks, and algorithms. New York: Springer-Verlag. 519.64 JUN 007905 152. Justesen, J. (2004). Course in error correcting codes. New Delhi: Hindustan book agency. 519.4 JUS 020251 153. Kailath, T. (1988). Lectures on Weiner and Kalman filtering. New York: Springer Science. 519.5 KAI 019850 154. Kailath, T. (2010). Linear estimation. London: Prentice Hall of India. 519.544 KAI 015906 155. Kaipio, J. (2005). Statistical and Computational Inverse Problems. New York: Springer. 515.357 KAI 019726 156. Kall, P. (2011). Stochastic linear programming: models, theory, and computation. Berlin: Springer-Verlag. 519.72 KAL 011458 157. Kalyanmoy, D. (2012). Optimization for engineering design: algorithms and examples (2nd ed.). New Delhi: PHI Learning. 519.602462 KAL 019798 158. Kampen, N. G. (2007). Stochastic processes in physics and chemistry. London: Elsevier. 519.202453 KAM 007774 159. Kandasamy, P. (2003). Probability, random variables and random processes. New Delhi: S. Chand and Company. 519.2 KAN 001725 160. Kanji, G. K. (2006). 100 statistical tests. London: Sage Publications. 519.56 KAN 007722

161. Kaplan, M. (2007). Chances are: adventures in probability. New York: Penguin Books. 519.2 KAP 016707 162. Kapur, J. N. (1960). Mathematical statistics. New Delhi: S. Chand & Co. 519.5 KAP 010612 163. Karian, Z. A. (2011). Handbook of fitting statistical distributions with R. Boca Raton, FL: CRC Press. 519.24 KAR 009708 164. Karlin, S. (1975). First course in stochastic processes (2nd ed.). New York: Academic Press. 519.2 KAR 020690 165. Karlin, S. (1981). Second course in stochastic processes. New York: Academic Press. 519.2 KAR 021799 166. Kay, S. M. (2005). Intuitive probability and random processes using MATLAB. New York: Springer Science. 519.20113 KAY 015419 167. Kay, S. M. (2010). Modern spectral estimation: theory and application. New Delhi: Pearson Education. 519.5 KAY 014416 168. Keen, K. J. (2010). Graphics for statistics and data analysis with R. Boca Raton: CRC Press. 515.50285 KEE 009789 169. Keller, G. (2009). Statistics for management and economics. New Delhi: Cengage Learning. 519.5 KEL 002532 170. Kelley, C. T. (1995). Iterative methods for linear and nonlinear equations. New Delhi: Society for Industrial and Applied Mathematics (SIAM). 519.4 KEL 003005 171. Kelly, F. (2014). Stochastic networks. Cambridge: Cambridge University Press. 519.2 KEL 018841 172. Khasminskii, R. (2012). Stochastic stability of differential equations. Heidelberg: Springer. 519.22 KHA 011460 173. Kinney, J. J. (2015). Probability: an introduction with statistical applications (2nd ed.). New York: John Wiley & Sons. 519.2 KIN 021832 174. Kirchgassner, G. (2007). Introduction to modern time series analysis. Berlin: Springer. 519.55 KIR 003171

175. Klafter, J. (2011). First steps in random walks: from tools to applications. Oxford: Oxford University Press. 519.282 KLA 019310 176. Klebaner, F. C. (2005). Introduction to stochastic calculus with applications. London: Imperial College Press. 519.23 KLE 011238 177. Kleinert, H. (2009). Path integrals in quantum mechanics, statistics, polymer physics, and financial markets. New jersey: World Scientific. 530.12 KLE 001949 178. Kleinrock, L. (1975). Queueing systems. New York: Wiley. 519.82 KLE 013960 179. Koller, D. (2009). Probabilistic graphical models: principles and techniques. Cambridge: MIT Press. 519.5420285 KOL 014899 180. Korb, K. B. (2011). Bayesian artificial intelligence. Boca Raton, FL: CRC Press. 519.542 KOR 010973 181. Korostelev, A. P. (2011). Mathematical statistics: asymptotic minimax theory. RI: American Mathematical Society. 519.5 KOR 013617 182. Korte, B. H. (2012). Combinatorial optimization: theory and algorithms. New York: Springer. 519.64 KOR 014597 183. Krishnan, V. (2014). Probability and random processes. New Delhi: Wiley. 519.2 KRI 018896 184. Krzanowski, W. J. (2000). Principles of multivariate analysis: a users perspective. New York: Oxford University Press. 519.535 KRZ 018566 185. Kubiak, T.M. (2009). Certified six sigma black belt handbook. New Delhi: Pearson Education. 658.4013 KUB 005427 186. Kuehl, R. O. (2000). Design of experiments: statistical principles of research design and analysis. Pacific Grove: Duxbury/Thomson Learning. 519.5 KUE 011806 187. Kuhn, H. W. (1997). Classics in game theory. New Jersey: Princeton University Press. 519.3 KUH 007999

188. Kuhn, M. (2013). Applied predictive modeling. New York: Springer-Verlag. 519.5 KUH 018333 189. Kullback, S. (1997). Information theory and statistics. New York: Dover Publication. 519.5 KUL 017311 190. Kundu, D. (2004). Statistical computing: existing methods and recent developments. New Delhi: Narosa Publishing House. 519.502 KUN 002932 191. Kushner, H. J (2003). Stochastic approximation and recursive algorithms and applications. New York: Springer. 519.2 KUS 011446 192. Kwon, R. H. (2014). Introduction to linear optimization and extensions with MATLAB®. Boca Raton: CRC Press. 519.72 KWO 017121 193. Lai, T. L. (2008). Statistical models and methods for financial markets. Berlin: Springer-Verlag. 332.501519 LAI 003732 194. Landau, L. D. (2011). Statistical physics. New Delhi: Elsevier. 530.13 LAN 009466 195. Landau, L.D. (2005). Statistical physics: course of theoretical physics (v.5). New Delhi: Butterworth-Heinmann.

531.19 LAN

000415

196. Lange, K. (2004). Optimization. Berlin: Springer-Verlag. 519.6 LAN 001749 197. Lattin, J. M. (2003). Analyzing multivariate data. New Delhi: Thomson. 519.535 LAT 002249 198. Lauritzen, S. L. (1996). Graphical models. New York: Oxford University Press. 519.538 LAU 022041 199. Lawler, G. F. (2006). Introduction to stochastic processes. Boca Raton: CRC Press. 519.2 LAW 017123 200. Leon-Garcia, A. (1994). Probability, random variables and random processes. New Delhi: Pearson Education. 519.2 LEO 005573 201. Leon-garcia, A. (2008). Probability, statistics, and random processes for electrical engineering. Upper Saddle River: PHI Learning. 519.20246213 LEO 011645

202. Levin, R. I. (1998). Statistic for management. New Delhi: Pearson Education. 519.5 LEV 005077 and 000861 203. Levine, D. M. (2008). Statistics for Six Sigma green belts: with Minitab and JMP. New Delhi: Pearson Education. 658.4013 005474 204. Liero, H. (2012). Introduction to the theory of statistical inference. Boca Raton: CRC Press. 519.54 LIE 017125 205. Liggett, T. M. (2010). Continuous time Markov processes: an introduction. RI: American Mathematical Society. 519.233 LIG 013592 206. Lind, D. A. (2008). Statistical techniques in business and economics. New Delhi: Tata McGraw Hill Education. 519.5 LIN 005835 207. Lipschutz, S. (1998). Schaums outline of theory and problems of introduction to probability and statistics. New Delhi: Tata McGraw Hill Education. 519.2 LIP 005641 208. Lipschutz, S. (2010). Schaum`s outlines Probability. New Delhi: Tata McGraw Hill. 519.2 LIP 006071 209. Liptser, R. S. (2001). Statistics of random processes. Berlin: Springer Science. 519.2 LIP 015596 210. Liu, G. P. (2008). Multi objective optimisation and control. New Delhi: PHI Learning. 519.6 LIU 006727 211. Long, J. S. (1997). Regression models for categorical and limited dependent variables. London: Sage Publications. 519.536 LON 020171 212. Luce, R. D. (1989). Games and decisions: introduction and critical survey. New York: Dover Publication. 519.3 LUC 004559 213. Luderer, B. (2003). Multivalued analysis and nonlinear programming problems with perturbations. Boston: Kluwer Academic Publishers. 519.76 LUD 015602 214. Luenberger, D. G. (1997). Optimization by vector space methods. New York: John Wiley & Sons. 519 LUE 021847

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*** Compiled by Library Date:10.08.2015