By John F. Monahan
With assurance gradually progressing in complexity, the textual content first presents examples of the final linear version, together with a number of regression types, one-way ANOVA, mixed-effects types, and time sequence versions. 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 offering the statistical instruments of speculation exams and self assurance durations, the writer analyzes combined versions, equivalent to two-way combined ANOVA, and the multivariate linear version. The appendices evaluate linear algebra basics and effects in addition to Lagrange multipliers.
This publication allows whole comprehension of the fabric by means of taking a basic, unifying method of the speculation, basics, and designated result of linear models.
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A Primer on Linear Models (Chapman & Hall/CRC Texts in Statistical Science) by John F. Monahan