By John F. Monahan
With insurance gradually progressing in complexity, the textual content first presents examples of the final linear version, together with a number of regression versions, one-way ANOVA, mixed-effects types, and time sequence types. It then introduces the fundamental algebra and geometry of the linear least squares challenge, sooner than delving into estimability and the Gauss–Markov version. After proposing the statistical instruments of speculation checks and self assurance durations, the writer analyzes combined versions, resembling two-way combined ANOVA, and the multivariate linear version. The appendices evaluate linear algebra basics and effects in addition to Lagrange multipliers.
This ebook allows whole comprehension of the cloth by means of taking a common, unifying method of the idea, basics, and designated result of linear models.
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Additional 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