It takes the average reader 6 hours and 10 minutes to read Bayesian Inference in Dynamic Econometric Models by Luc Bauwens
Assuming a reading speed of 250 words per minute. Learn more
This book contains an up-to-date coverage of the last twenty years advances in Bayesian inference in econometrics, with an emphasis on dynamic models. It shows how to treat Bayesian inference in non linear models, by integrating the useful developments of numerical integration techniques based on simulations (such as Markov Chain Monte Carlo methods), and the long available analytical results of Bayesian inference for linear regression models. It thus covers a broad range of rather recent models for economic time series, such as non linear models, autoregressive conditional heteroskedastic regressions, and cointegrated vector autoregressive models. It contains also an extensive chapter on unit root inference from the Bayesian viewpoint. Several examples illustrate the methods.
Bayesian Inference in Dynamic Econometric Models by Luc Bauwens is 370 pages long, and a total of 92,500 words.
This makes it 125% the length of the average book. It also has 113% more words than the average book.
The average oral reading speed is 183 words per minute. This means it takes 8 hours and 25 minutes to read Bayesian Inference in Dynamic Econometric Models aloud.
Bayesian Inference in Dynamic Econometric Models is suitable for students ages 12 and up.
Note that there may be other factors that effect this rating besides length that are not factored in on this page. This may include things like complex language or sensitive topics not suitable for students of certain ages.
When deciding what to show young students always use your best judgement and consult a professional.
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