search for: hedonic

...cients Models on Unbalanced Panel Data. I managed to fit such models on balanced panel data (the example from the "plm" vignette), but I failed to do so on my real, unbalanced panel data. I can reproduce the error on a modified example from the vignette: > require(plm) > data("Hedonic") > Hed <- pvcm(mv ~ crim + zn + indus + chas + nox + rm + age + dis +rad + tax + ptratio + blacks + lstat, Hedonic, model = "within",index = "townid") Error in FUN(X[[1L]], ...) : insufficient number of observations > ##it fails for both FE and RE cases > Hed &...

...uot;kinship is loaded" Loading required package: Formula Loading required package: MASS Loading required package: sandwich Loading required package: zoo Attaching package: 'zoo' The following object(s) are masked from package:base : as.Date.numeric > library(Ecdat) > data(Hedonic) > pdata.frame(Hedonic, "townid") Error: could not find function "pdata.frame" > >From here, I decided to try using plm.data, which worked > h2 <- plm.data(Hedonic, "townid") However, doing a summary of the h2 object, it was not as in the plmEN.pdf ex...

...I would like to implement a spatial quantile regression using instrumental variable estimation (according to Su and Yang (2007), Instrumental variable quantile estimation of spatial autoregressive models, SMU economics & statistis working paper series, 2007, 05-2007, p.35 ). I am applying the hedonic pricing method on land transactions in Luxembourg. My original data set contains 4335 observations. I'm quite new to R and would like to ask if someone has implemented the method proposed by Su and Yang in R or if anyone could give me a hint on the different codes and steps? Please find attach...

Since I have a mixture of RH 7.1, 7.2, 7.3 and Advanced Server 2.1 boxes, I've made a set of RPMs for those platforms. I do not have a RedHat 8.0 box to make RPMs. Since RedHat <= 7.2 is out of support by RedHat, I don't think we'll see any officially created RPMs (but I could be wrong about that) so I thought I'd offer these to the general community. These were all built

hi - i just started using R as i am trying to figure out how perform a linear regression on a huge matrix. i am sure this topic has passed through the email list before but could not find anything in the archives. i have a matrix that is 2,000,000 x 170,000 the values right now are arbitray. i try to allocate this on a x86_64 machine with 16G of ram and i get the following: > x <-