𝔖 Bobbio Scriptorium
✦   LIBER   ✦

Koch, K.R.: Parameter estimation and hypothesis testing in linear models

✍ Scribed by P. Schönfeld

Book ID
112938822
Publisher
Springer-Verlag
Year
1989
Tongue
English
Weight
60 KB
Volume
30
Category
Article
ISSN
0932-5026

No coin nor oath required. For personal study only.

📜 SIMILAR VOLUMES

Biased estimation and hypothesis testing
Biased estimation and hypothesis testing in linear regression
✍ Peter Stahlecker; Karsten Schmidt 📂 Article 📅 1996 🏛 Springer Netherlands 🌐 English ⚖ 243 KB

We consider a test of the simple hypothesis/3 = /3o based on some biased estimator. Under a certain condition the corresponding test statistic coincides with the usual F-statistic based on the least squares estimator. Surprisingly, this condition is met by several well-known biased estimators.

Parameter estimation and hypothesis test
Parameter estimation and hypothesis testing in stationary vector time series
✍ Yoshihide Kakizawa 📂 Article 📅 1997 🏛 Elsevier Science 🌐 English ⚖ 474 KB

Statistical inference for stationary time series is often based on the maximum likelihood principle, i.e., the maximization of the (quasi) likelihood of observations derived on Gaussian assumptions, although no such distributional assumptions are made. In this paper, we define the disparity measure

Estimating and Testing Linear Hypotheses
Estimating and Testing Linear Hypotheses on Parameters in the Log-linear Model
✍ Kullback, S. 📂 Article 📅 1973 🏛 Wiley (John Wiley & Sons) ⚖ 790 KB

It is a consequence of the minimum discrimination information theorem, that minimum discrimination information distributions are formulated as members of an exponential family (CAMPBELL, 1970; KULLBACK, 1959). For applications to the analysis of contingency tables i t is useful to express the expone