By John F. Monahan
With assurance progressively progressing in complexity, the textual content first offers examples of the overall linear version, together with a number of regression versions, one-way ANOVA, mixed-effects types, and time sequence types. It then introduces the elemental algebra and geometry of the linear least squares challenge, ahead of delving into estimability and the Gauss–Markov version. After offering the statistical instruments of speculation checks and self assurance periods, the writer analyzes combined types, corresponding to two-way combined ANOVA, and the multivariate linear version. The appendices evaluate linear algebra basics and effects in addition to Lagrange multipliers.
This ebook permits entire comprehension of the fabric by means of taking a common, unifying method of the idea, basics, and special 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