similar to: gam parameter predictions --Sorry for double posting

Hi all, I have this (non-working) script: dataTest <- data.frame(col1=c(1,2,3)) new.data <- c(1,2) name <- "test" n.row <- dim(dataTest)[1] length(new.data) <- n.row names(new.data) <- name cbind(dataTest, name=new.data) print(dataTest) and would like to bind the new column 'new.data' to 'dataTest' by using the value of the variable 'name' as

Hi, I am trying to use svm for regression data. this is how my data looks like: >dataTrain x y z 1 4 6 2 5 4 3 7 5 >classTrain a 2 3 4 >dataTest x y z 1 7 2 2 8 3 >classTest a 3 4 5 building the model model<-svm(dataTrain,classTrain,type="nu-regression") pred <- predict(model, dataTest) > pred 1 2 3.008842 3.120078 I

Hi all, I have exactly the same problem as the OP and tried the solution below, but I still get the error: 'Username IUCNNL\PC050$ is invalid on this system'. Should I map useraccount, enable Guest account, chang eunix directory permissions or things like that? Problem: My Windows 10 computers' machine accounts cannot acces shares on a domain member (samba 4.6 , id map = ad, centos

Dear list, I'd like to use multiple imputations to try and save a somewhat badly mangled dataset (lousy data collection, worse than lousy monitoring, you know that drill... especially when I am consulted for the first time about one year *after* data collection). My dataset has 231 observations of 53 variables, of which only a very few has no missing data. Most variables have 5-10% of

Hi, I have a table like that: > datatest var1 var2 var3 1 1 1 1 2 3 1 2 3 8 1 3 4 6 1 4 5 10 1 5 6 2 2 1 7 4 2 2 8 6 2 3 9 8 2 4 10 10 2 5 I need to create another table based on that with the rules: take a random sample by var2==1 (2 sample rows for example): var1 var2 var3 1 1

I expected, that I will get the same prediction, if I multiply the weights for all classes with a constant factor, but I got different results. Please look for the following code. > library(e1071) > data(Glass, package = "mlbench") > index <- 1:nrow(Glass) > testindex <- sample(index, trunc(length(index)/5)) > testset <- Glass[testindex, ] > trainset <-

Hi all, I am running some linear mixed models for longitudinal data using the nlme package. Part of the code I've developed tests for differences among models using the anova function, but I can't simply pass the corresponding lme objects as parameters to the anova function because some of the models do not converge and others are retained for comparison only if certain criteria are met.

Dear All, could someone please shed some light on the use of the .C or .Fortran function: I am trying load and running on R the following function // psi.cpp -- psi function for real arguments. // Algorithms and coefficient values from "Computation of Special // Functions", Zhang and Jin, John Wiley and Sons, 1996. // // (C) 2003, C. Bond. All rights reserved. // //

Hello, I've a question concerning the display of interval data. A sample dataset where X is an interval between Xa and Xb which should be displayed: Y=c(15,14,23,18,19,9,19,13) Xa=c(17,22,21,18,19,25,8,19) Xb=c(22,22,29,34,19,26,17,22) X = (Xa+Xb)/2 It's easily possible to plot the mean of the interval like: plot(X,Y) afterwards I can create lines for the interval with:

Dear all This may be obvious, but I cannot get it working. I'm trying to subset & sort a data frame in one go. x <- iris x$Species1 <- as.character(x$Species) ##subsetting alone works fine with(x, x[Sepal.Length==6.7,]) ##sorting alone works fine with(x, x[order(Sepal.Length, rev(sort(Species1))),]) ##gets subsetted, but not sorted as expected with(x, x[(Sepal.Length==6.7) &

Hi everyone, ? I am trying to get a point of intersection between a polyline and a straight line ?.. and get the x and y coordinates of this point. For exemplification consider this: ? ? set.seed(123) ? k1 <-rnorm(100, mean=1.77, sd=3.33) ?k1 <- sort(k1) q1 <- rnorm(100, mean=2.37, sd=0.74) q1 <- sort(q1, decreasing = TRUE) plot(k1, q1, xlim <- c((min(k1)-5),

Dear all, I have a function to optimize for a set of parameters and want to set a constraint on only one parameter. Here is my function. What I want to do is estimate the parameters of a bivariate normal distribution where the correlation has to be between -1 and 1. Would you please advise how to revise it? ex=function(s,prob,theta1,theta,xa,xb,xc,xd,t,delta) { expo1=

Hello all. I am a novice Ruby on Rails programmer, starting my first project using a legacy Oracle 10 database. Using ''reverse_scaffold'' I have created the models/controllers/views for my existing Oracle tables. All seems to work well, using /model/index, /model/show for most of my tables, *except* when one of the tables contains a Oracle ''date'' column, for

On Mon, 20 Nov 2017 07:59:14 -0700 (MST) tomict via samba <samba at lists.samba.org> wrote: > Below is relevant info (I think) for my case > > What I did/tried: > -With ADUC (WS 2012) I added NIS domain 'samdom' to the Unix > attributes of users, groups, and also to computers (is the latter > nesecary?) -I test the connection to the shares as system user on the

Hi any, Can some please detail me the createX command in bayesm package? To make things easy for you to help me, let me put forward my problem Suppose I have 3 covariates (say X matrix) and my Y has 3 categories say (1,2,3). Now from the CreateX I understand that the data matrix say 'Xa' must be of dimension n* (naxp), where 'na' is the number of variables and 'p' is

Hi all I have a 3d array containing missing values. > Xa , , 1 [,1] [,2] [1,] 1 3 [2,] NA 4 , , 2 [,1] [,2] [1,] 5 7 [2,] NA NA , , 3 [,1] [,2] [1,] 9 11 [2,] 10 12 I want to replace the missing values with the mean, but the mean of each 'page' in the array (wrong terminology I'm sure). So - for the array above - [2,1,2] and

Dear All: Urgent help is needed. I have a data set in matrix format of three columns: X, Y and index of four groups (1,2,3,4). What I need to do is the following; 1- How I can subtract the sample mean of each group indexed 1,2,3,4 from the corresponding data values of this group and create new columns say X-sample mean and Y-sample mean? I tried to use the "tapply" but

Hello Gurus I have two correlation matrices 'xa' and 'xb' set.seed(100) d=cbind(x=rnorm(20)+1, x1=rnorm(20)+1, x2=rnorm(20)+1) d1=cbind(x=rnorm(20)+2, x1=rnorm(20)+2, x2=rnorm(20)+2) xa=cor(d,use='complete') xb=cor(d1,use='complete') I want to combine these two to get a third matrix which should have half values from 'xa' and half

Dear all Is there a simpler method to achieve the following: When I obtain an empty data.frame after subsetting, I need for it to contain one line of NAs. Here's a dummy example: > (.xb <- iris[ iris$Species=='zz', ]) [1] Sepal.Length Sepal.Width Petal.Length Petal.Width Species <0 rows> (or 0-length row.names) > dim(.xb) [1] 0 5 > (.xa <-

Dear all I have a 'character' vector containing mixed formats (thanks Excel!) and I'd like to translate it into a default "%Y-%m-%d" Date vector. x <- c("1/3/2005", "13/04/2004", "2/5/2005", "2/5/2005", "7/5/2007", "22/04/2004", "21/04/2005", "20080430", "13/05/2003",