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 versions, one-way ANOVA, mixed-effects versions, and time sequence types. It then introduces the fundamental algebra and geometry of the linear least squares challenge, earlier than delving into estimability and the Gauss–Markov version. After offering the statistical instruments of speculation checks and self belief periods, the writer analyzes combined versions, comparable to two-way combined ANOVA, and the multivariate linear version. The appendices overview linear algebra basics and effects in addition to Lagrange multipliers.
This ebook allows entire comprehension of the cloth via taking a normal, unifying method of the speculation, basics, and specific 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