By John F. Monahan
With insurance gradually progressing in complexity, the textual content first offers examples of the final linear version, together with a number of regression types, one-way ANOVA, mixed-effects types, and time sequence types. It then introduces the fundamental algebra and geometry of the linear least squares challenge, ahead of delving into estimability and the Gauss–Markov version. After proposing the statistical instruments of speculation checks and self assurance periods, the writer analyzes combined types, resembling two-way combined ANOVA, and the multivariate linear version. The appendices evaluate linear algebra basics and effects in addition to Lagrange multipliers.
This booklet permits whole comprehension of the cloth by way of taking a normal, unifying method of the speculation, basics, and precise result of linear models.
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Extra resources for A Primer on Linear Models (Chapman & Hall/CRC Texts in Statistical Science)
A Primer on Linear Models (Chapman & Hall/CRC Texts in Statistical Science) by John F. Monahan