000 02236nam a2200385 i 4500
008 040513t20042004nyua b 001 0 eng
015 _a04,N13,0258
_2dnb
020 _a0387212396
_q(acid-free paper)
020 _a9780387212395
_q(acid-free paper)
035 _a(OCoLC)55488084
040 _aDLC
_beng
_cDLC
_dYDX
_dNDD
_dOHX
_dMUQ
_dBAKER
_dNLGGC
_dUBA
_dBTCTA
_dYDXCP
_dOCLCG
_dIG#
_dHEBIS
_dTVG
_dDEBSZ
_dRRP
_dSINTU
_dBDX
_dOCLCF
_dOCLCO
_dOCLCQ
_dOCLCO
_dUtOrBLW
049 _aBAUN_MERKEZ
050 0 4 _aQA276
_b.R575 2004
082 0 0 _222
100 1 _aRobert, Christian P.,
_d1961-
245 1 0 _aMonte Carlo statistical methods /
_cChristian P. Robert, George Casella
250 _aSecond edition
264 1 _aNew York :
_bSpringer,
_c[2004]
264 4 _c©2004
300 _axxx, 645 pages :
_billustrations ;
_c24 cm
336 _atext
_btxt
_2rdacontent
337 _aunmediated
_bn
_2rdamedia
338 _avolume
_bnc
_2rdacarrier
490 1 _aSpringer texts in statistics
504 _aIncludes bibliographical references (pages 591-622) and indexes
505 0 0 _t-- Random Variable Generation
_t-- Monte Carlo Integration
_t-- Controlling Monte Carlo Variance
_t-- Monte Carlo Optimization
_t-- Markov Chains
_t-- Metropolis-Hastings Algorithm
_t-- Slice Sampler
_t-- Two-Stage Gibbs Sampler
_t-- Multi-Stage Gibbs Sampler
_t-- Variable Dimension Models and Reversible Jump
_t-- Diagnosing Convergence
_t-- Perfect Sampling
_t-- Iterated and Sequential Importance Sampling
520 0 _a"Monte Carlo statistical methods, particularly those based on Markov chains, are now an essential component of the standard set of techniques used by statisticians. This new edition has been revised towards a coherent and flowing coverage of these simulation techniques, with incorporation of the most recent developments in the field. In particular, the introductory coverage of random variable generation has been totally revised, with many concepts being unified through a fundamental theorem of simulation"--Back cover
650 0 _aMathematical statistics
650 0 _aMonte Carlo method
700 1 _aCasella, George
830 0 _978445
_aSpringer texts in statistics
900 _a35549
900 _bsatın
942 _2lcc
_cKT
999 _c32753
_d32753