Perception as Bayesian inference /

Bayesian decision problems and Markov chains / by Martin, James John

Optimum inductive methods : a study in inductive probability, Bayesian statistics and verisimilitude / by Festa, Roberto

The Theory and practice of econometrics /

Table of Contents: “…Sampling theory and Bayesian approaches to inference. -- The Classical Inference Approach for the General Linear Model. -- Statistical Decision Theory and Biased Estimation. -- The Bayesian Approach to Inference. -- Inference in general statistical models and time series. -- Some Asymptotic Theory and Other General Results for the Linear Statistical Model. -- Nonlinear Statistical Models. -- Time Series. -- Dynamic specifications. -- Autocorrelation. -- Finite Distributed Lags. -- Infinite Distributed Lags. -- Some alternative covariance structures. -- Heteroskedasticity. -- Disturbance-Related Sets of Regression Equations. -- Inference in Models that Combine Time Series and Cross-Sectional Data. -- Inference in simultaneous equation models. -- Specification and Identification in Simultaneous Equation Models. -- Estimation and Inference in a System of Simultaneous Equations. -- Multiple Time Series and Systems of Dynamic Simultaneous Equations. -- Further model extensions. -- Unobservable Variables. -- Qualitative and Limited Dependent Variable Models. -- Varying and Random Coefficient Models. -- Non-Normal Disturbances. -- On Selecting the Set of Aggressors. -- Multicollinearity. -- Appendices.…”