Titlebook: Learning Regression Analysis by Simulation; Kunio Takezawa Book 2014 Springer Japan 2014 Akaike‘s Information Criterion (AIC).basic concep

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箴言

正式演說

Simple Regression,. where . ( = ..) is a residual. This process yields the regression equation: . where .. is the intercept and .. is the gradient (slope). Each data point is represented as . Values such as .. and .. are called regression coefficients. The “ . ” (hat) of . and . indicates that these values are estimates.

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同音

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Linear Mixed Model, are column matrices for which the lengths are .. and can be expressed in the form: . Here, {..} (1 ≤ . ≤ ..) are observations of the .-th treatment (1 ≤ . ≤ .); {..} (1 ≤ . ≤ .) are realizations from .(0, ..) (normal distribution with mean 0 and variance ..).

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a frames, and so on..For example, when a statistical theory indicates that an event happens with a 5 % probability, readers can confirm the fact using R programs that this event actually occurs with roughly that probability, by handling data generated by pseudo-random numbers. Simulation gives readers populat978-4-431-56143-9978-4-431-54321-3

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