[学科前沿] Discrete Choice Methods with Simulation by Kenneth E. Train [推广有奖]

<p>[Point=10][/Point]</p><p> </p><p><font size="3"><strong>Discrete Choice Methods with Simulation</strong></font></p><p><br/>This book describes the new generation of discrete choice meth-<br/>ods, focusing on the many advances that are made possible by<br/>simulation. Researchers use these statistical methods to examine<br/>the choices that consumers, households, firms, and other agents<br/>make. Each of the major models is covered: logit, generalized<br/>extreme value (including nested and cross-nested logits), probit,<br/>and mixed logit, plus a variety of specifications that build on<br/>these  basics.  Simulation-assisted  estimation  procedures  are<br/>investigated  and  compared,  including  maximum  simulated<br/>likelihood, the method of simulated moments, and the method<br/>of  simulated  scores.  Procedures  for  drawing  from  densities<br/>are  described,  including  variance  reduction  techniques  such<br/>as antithetics and Halton draws. Recent advances in Bayesian<br/>procedures are explored, including the use of the Metropolis–<br/>Hastings algorithm and its variant Gibbs sampling. No other<br/>book incorporates all these topics, which have risen in the past<br/>20 years. The procedures are applicable in many fields, includ-<br/>ing energy, transportation, environmental studies, health, labor,<br/>and marketing.</p> 254348.zip (1.75 MB) 本附件包括：

• bib.pdf
• ch1.pdf
• ch10.pdf
• ch11.pdf
• ch12.pdf
• ch2.pdf
• ch3.pdf
• ch4.pdf
• ch5.pdf
• ch6.pdf
• ch7.pdf
• ch8.pdf
• ch9.pdf
• index.pdf
• pre.pdf

2008-10-8 22:53:00 上传

Discrete Choice Methods with Simulation by Kenneth E. Train

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