January 2009
Beginner
264 pages
8h 12m
English
Content preview from Computational Statistics
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74 REGRESSION
See Also
summary.lm for summaries and anova.lm for the ANOVA table; aov for a different interface.
The generic functions coef, effects, residuals, fitted, vcov.
predict.lm (via predict) for prediction, including confidence and prediction intervals;
confint for confidence intervals of parameters.
lm.influence for regression diagnostics, and glm for generalized linear models.
The underlying low level functions, lm.fit for plain, and lm.wfit for weighted
regression fitting.
More lm() examples are available e.g., in anscombe, attitude, freeny, LifeCycleSavings,
longley, stackloss, swiss.
biglm in package biglm for an alternative way to fit linear ...
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O’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.Julian F.
I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.Amir M.
I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.