search for: bx1

Hello, Is there a simple way of stacking/merging two dataframes in R? I want to stack them piece-wise, not simply add one whole dataframe to the bottom of the other. I want to create as follows: x.frame: aX1 bX1 cX1 ... zX1 aX2 bX2 cX2 ... zX2 ... ... ... ... ... aX99 bX99 cX99 ... zX99 y.frame: aY1 bY1 cY1 ... zY1 aY2 bY2 cY2 ... zY2 ... ... ... ... ... aY99 bY99 cY99 ... zY99 new.frame: aX1 bX1 cX1 ... zX1 aY1 bY1 cY1 ... zY1 aX2 bX2 cX2 ... zX2 aY2 bY2 cY2 ... tY2 ... ......

Hello I try to find probability values of some predictor combinations using logistic reg. in response level. Firstly I found coefficients by glm function. Then I followed two ways to get probability values: 1- probility <- exp(X0+bX1+cX2+...)/((1+exp(X0+bX1+cX2+...)) 2- probility <- predict(glm.obj,type="resp") Should have these two given same result ? if so, I did not have. Why ? Does anyone have any idea ? thanks in advance Ahmet Temiz TURKEY ______________________________________ _______________________...

Hi there, Just wondering if anyone has any tips for using arrays? I am trying to convert the following SAS code to R: data A2; set A1; by subject_id; retain BX1-BX10 i; array b(1:10) BX1-BX10 ; if first.subject_id then do ; do j=1 to 10; b(j) = .; end; i=1; end; b(i) = BX; i = i+1; if last.subject_id then output; run ; Many thanks in advance, Bronagh [[alternative HTML version del...

Hi, Suppose I've got a matrix, and the first few elements look like "x1 + x3 + x4 + x5 + x1:x3 + x1:x4" "x1 + x2 + x3 + x5 + x1:x2 + x1:x5" "x1 + x3 + x4 + x5 + x1:x3 + x1:x5" and so on (have got terms from x1 ~ x14). If I want to replace all the x1 with i7, all x2 with i14, all x3 with i13, for example. Is there an easy way? I tried to put what I want

...tion parameter empty, I assume a backward multiple reg is implemented), 12 Xia-a remain in the final model where X1 is still present, the X1 beta coefficient becomes = --0.43402 (se=0.06847) I did not expect such a drastic change (4 times smaller) in the beta coeff. from "lm" with X1 (bx1=-0.08) to "step" with final 12 Xis including X1 (bx1=--0.43402). I understand that step function is producing partial reg coeff, when all other Xi-s are held constant, but is there any good reason why X1 in a multivariate reg. can become so significant (from lm px1=0.00296 ** to step...

Dear all: Y=a+bX1+cX2 In the Gee (Generalized Estimation Equation) arguments: The arument Corstr has sveral choices: "independence" "fixed" "stat_M_dep" "non_stat_M_dep" "exchangeable" "AR-M" "unstructured" What does each...

I have a program which is doing a few thousand runs of lm(). Suppose it is a simple model y = a + bx1 + cx2 + e I have the R object "d" where d <- summary(lm(y ~ x1 + x2)) I would like to obtain Var(x2) out of "d". How might I do it? I can, of course, always do sd(x2). But it would be much more convenient if I could snoop around the contents of summary.lm and extract Va...

Dear all, I am trying to fit a mixed-effects non linear regression, but I have some trouble with it. My data are a balanced panel of 904 subjects with 8 observations (at regular periods) per subject. The functional form of my model is Y=Aexp(-BX1)X2 +e. I want to allow parameters A and B to vary among subjects and also include an autocorrelation term. I have already fitted a standard nonlinear regression to the data, but I keep having problems with NLME. I have defined my data as a groupedData object, and when I try to fit the model I get...

Hei Group, I want to compare the relative importance of predictors in a multiple linear regression y~a+bx1+cx2... However, bptest indicates heteroskedasticity of my model. I therefore perform a robust regression (rlm), in combination with bootstrapping (as outlined in J. Fox, Bootstrapping Regression Models). Now I want to compare the relative importance of my predictors. Can I rely on the output of &...

Hi, I'm looking for a super-duper fast mean/sum binning implementation available in R, and before implementing z = binnedMeans(x y) in native code myself, does any one know of an existing function/package for this? I'm sure it already exists. So, given data (x,y) and B bins bx[1] < bx[2] < ... < bx[B] < bx[B+1], I'd like to calculate the binned means (or sums)