The lm function is used to fit linear models in R. It can be used to carry out regression, single stratum analysis of variance and analysis of covariance.
I'm trying to add a fitted quadratic curve to a plot. abline(lm(data~factor+I(factor^2))) The regression which …
r lmI have a few datapoints (x and y) that seem to have a logarithmic relationship. > mydata x y 1 0 123 2 2 116 3 4 113 4 15 100 5 48 87 6 75 84 7 122 77 > …
r curve-fitting lm nlsI ran a regression: CopierDataRegression <- lm(V1~V2, data=CopierData1) and my task was to obtain a 90% confidence …
r regression linear-regression prediction lmI have a vector Y containing future returns and a vector X contain current returns. The last Y element is …
r lmI am fitting a model to factor data and predicting. If the newdata in predict.lm() contains a single factor …
r regression linear-regression lmI know there is a small difference between $sigma and the concept of root mean squared error. So, i am …
r regression linear-regression lmIs it possible to set a stepwise linear model to use the BIC criteria rather than AIC? I've been trying …
r lm