search for: regresson

Dear All,   wondering if you know of a good resource on-line to read on interpreting the parameter estimate result "statistics' for the output of a nonlinear regression model. I am specifically having a hard time finding information on the interpretation  of t value and Pr > /t/ in layman terms.   any direction or help would be greatly apreciated,   thanks,   Andras [[alternative

...3 0 0 80 4 0 33.33 20 Pointers appreciated. 2. A student said here's y, a vector representing a time series, and here's x, a vector representing a time series. I want to do a conventional regression of y on the lag of x. In sas you do xlag=lag(x) and then use xlag in a regresson. I just want something simple like lm(y~lag(x)). But in R base there's no lag. So I can get it the old fashioned way: > xx <- c(NA,x) > modl <- lm(y~xx[1:length(y)]) > summary(modl) One sidenote is that summary does not include any mention of the fact that 1 observation w...

Not sure what you are trying to do here. The immediate issue is that you are getting 'y' on the RHS, because that is the 1st column in Dataset. So "for (i in 2:3)" might be closer to intention. However, a 0/1 regresson with no intercept implies that the mean for the "0" group is zero, and with two regressors that the mean is zero for the (0,0) group. Looking at the data, this is quite clearly not the case. I suppose you may have intended to fit the models _with_ the intercept and then _ignore_ the inte...

R-packages leaps and subselect implement various methods of selecting best or good subsets of predictor variables for linear regression models, but they do not seem to be applicable to logistic regression models. Does anyone know of software for finding good subsets of predictor variables for linear regression models? Thanks. -Ben p.s., The leaps package references "Subset Selection

Hi there, it might be a very simple question and I'd be glad to even get a link to some useful documentation... I have several data sets, I'd like to fit to a gaussian distribution. I've tried to give an estimate of the mean and the sd of this distribution but still, I run into problems if these estimates are not close enough. For example, nls() breaks with this message: singular

Dear R-experts, Here below my R code working with quite a few warnings.? x11 and x12 are dichotomous variable (0=no and 1=yes). I substract 1 to ignore intercept. I would like not to ignore intercept. How to modify my R code because if I just remove -1 it does not work? y= c(32,45,65,34,23,43,65,76,87,98,7,867,56,45,65,76,88,34,55,66) x11=c(0,1,1,0,0,1,1,1,0,0,1,0,0,1,0,0,1,1,0,1)

...sec=krb5,vers=4.1 vdmpp1.ad.fvg.lnf.it:/users /home And hureay it works ;-) and if not, mail me again. :-( Last, if you see in you logs. lkmapd[304]: open pipe file /run/rpc_pipefs/nfs/blocklayout failed: No such file or directory You can ignore this, its known, just wait for the bug fix, its a regresson bug in nfs. And in reply to the new mail. You nfs stalled, then it gets mask to prevent other errors. systemctl unmask nfs-common systemctl enable nfs-common If you keep hitting problems with the nfs server/client apt-get remove --auto-remove --purge nfs-common nfs-kernel-server Clear your n...

Hi group, I found a module for adaptive kernel density estimation for Stata users, but unfortunetly I don't have access to Stata, can I find a similar approach using R? Thank u so much 4 ur time. [[alternative HTML version deleted]]