Hello, Is there anyway one can have more than 11 independent variables in a regression model? To hopefully illustrate: with 13 predictors in my model, the last 2 coefficient estimates are "NA". When I view the summary, it indicates that 2 coefficients are "not defined because of singularities". I am using the command: mod <- lm(y ~ ., data = volumes[,3:22]) I am fairly new to R so I don't know if my issue is something inherent to R or my modeling approach. Any insight would be most appreciated... Thanks in advance
Your data won't support it. It has nothing to do with R or any other decent linear regression fitting software. I've seen up to 60 indep variables, with a data set for which it almost made sense. best, -tony On 5/8/05, Jim BRINDLE <j_brindle at hotmail.com> wrote:> Hello, > > Is there anyway one can have more than 11 independent variables in a > regression model? To hopefully illustrate: with 13 predictors in my model, > the last 2 coefficient estimates are "NA". When I view the summary, it > indicates that 2 coefficients are "not defined because of singularities". I > am using the command: > > mod <- lm(y ~ ., data = volumes[,3:22]) > > I am fairly new to R so I don't know if my issue is something inherent to R > or my modeling approach. > > Any insight would be most appreciated... Thanks in advance > > ______________________________________________ > R-help at stat.math.ethz.ch mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html >-- best, -tony "Commit early,commit often, and commit in a repository from which we can easily roll-back your mistakes" (AJR, 4Jan05). A.J. Rossini blindglobe at gmail.com
Jim BRINDLE wrote:> Hello, > > Is there anyway one can have more than 11 independent variables in a > regression model? To hopefully illustrate: with 13 predictors in my model, > the last 2 coefficient estimates are "NA". When I view the summary, it > indicates that 2 coefficients are "not defined because of singularities". I > am using the command: > > mod <- lm(y ~ ., data = volumes[,3:22]) > > I am fairly new to R so I don't know if my issue is something inherent to R > or my modeling approach. > > Any insight would be most appreciated... Thanks in advanceThe question has not much to do with R, but with linear models. Probably you don't have enough observations in order to estimate those coefficients. Please read some statistical textbook on the topic of degrees of freedom in linear models and regression analysis. Uwe Ligges> ______________________________________________ > R-help at stat.math.ethz.ch mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html