similar to: Ltsreg and nsamp="exact"

Displaying 20 results from an estimated 1200 matches similar to: "Ltsreg and nsamp="exact""

2003 Feb 10
2
problems using lqs()
Dear List-members, I found a strange behaviour in the lqs function. Suppose I have the following data: y <- c(7.6, 7.7, 4.3, 5.9, 5.0, 6.5, 8.3, 8.2, 13.2, 12.6, 10.4, 10.8, 13.1, 12.3, 10.4, 10.5, 7.7, 9.5, 12.0, 12.6, 13.6, 14.1, 13.5, 11.5, 12.0, 13.0, 14.1, 15.1) x1 <- c(8.2, 7.6,, 4.6, 4.3, 5.9, 5.0, 6.5, 8.3, 10.1, 13.2, 12.6, 10.4, 10.8, 13.1, 13.3, 10.4, 10.5, 7.7, 10.0, 12.0,
2011 Dec 06
2
Why can't I figure this out? :S
Hi, so I don't speak computer and I have no idea what this code is telling the program to do, but I apparently need to be able to find and isolate influencial observations. Problem, I have no idea what the error means and where it may be from in the code. error I get is below the code { ## OLS results NameC<- lm(gpanew~female+female:lastinit+agenew+canadian+mom_ed+yearstudy) ## default:
2001 Nov 29
0
ltsreg warnings (PR#1184)
Full_Name: Charles J. Geyer Version: 1.3.1 OS: linux-gnu-i686 Submission from: (NULL) (134.84.86.22) ltsreg gives incomprehensible (to me) warnings A homework problem for nonparametrics ########## start example ########## library(bootstrap) data(cell) names(cell) attach(cell) library(lqs) plot(V1, V2) fred <- ltsreg(V2 ~ V1 + I(V1^2)) curve(predict(fred, data.frame(V1 = x)), add = TRUE)
2003 Mar 03
1
using data() in an example
Hi all, I'm trying to put together examples in an R package, and am having trouble reading data from the package's data directory. The data are in comma-separated variable files, so to read a file like gw.csv, I include in the data directory both bailey.csv and a file bailey.R which contains: bailey <- read.csv("bailey.csv",na.strings="."); so that typing
2009 Jan 17
2
Confidence Interval
I am new to R and Im some trouble with the following question... Generate 100 standard normal N(0,1) samples of size 100, X1(k),...,X100(k) where k=1,...,100 (The k is and indicie in brackets) Calculate the sample mean for each sample. For each sample mean Xbark the 0.95-confidence interval for the mean mew=0 is given by... Ik= ( Xbark plus or minus 1.96/10) Find the number of intervals such
2012 Jan 23
1
R not giving significance tests for coefficients/estimates?
> 3x4 Error: unexpected symbol in "3x4" R has no idea that you equate "x" as multiplication.. use an astrix > 3*4 [1] 12 dominic wrote > > This is basically my code: > > library(MASS) > lmsreg(formula = b0 ~ b1 + b3 + b1xb2, data=mydata) > > b1xb2 is an interaction but it was the centered value for a continuous > variable times a
2003 Jun 17
2
outlier
Hi, I want to calculate the R-squared between two variables. Can you advice me how to identify and remove the outliers before performing R-squared calculation? Thanks, Kan --------------------------------- SBC Yahoo! DSL - Now only $29.95 per month! [[alternate HTML version deleted]]
2006 Apr 27
1
? bug in 'sample' (PR#8813)
I have found that specifying different "sizes" in the sample command has a funny effect on the random sampling. The code below is a condensed version of a function I wrote to simulate a bootstrap method. For simplicity, I eliminated the internal bootstrap loop, but kept a statement to draw one bootstrap sample, because this is where the problem occurs. The output (mean(y)^2) should be
2002 Jun 03
1
LTS
Hello I want to ask if the estimator method LTS (Least Trimmed Squares) is implemented in R. I've found the lqs(y~x,method = c("lts")) tool that implements LTS but minimazing the sum of the `quantile' smallest squared residuals. I don't know if this is the same as the clasical LTS, if it is, where do I set the trim (h value to trim the LS sum)? I'll be waiting
2005 Sep 01
0
Robust Regression - LTS
Hi, I am using robust regression, i.e. model.robust<-ltsreg(MXD~ORR,data=DATA). My question:- is there any way to determine the Robust Multiple R-Squared (as returned in the summary output in splus)? I found an equivalent model in the rrcov package which included R-square, residuals etc in it's list of components, but when I used this package the only results returned were equivalent to
2012 Dec 20
3
Optmatch Package Question
Hello , My optmatch package is loaded on R and otherwise running fine. I get an error after lcds successfully completes a logistic regression and I then try to obtain a propensity score: pdist <- pscore.dist(lcds) Error: could not find function "pscore.dist" Does anyone know if pscore.dist is part of the optmatch package, or is it contained in another package that I need to
2004 May 21
2
Help with Plotting Function
Dear List: I cannot seem to find a way to plot my data correctly. I have a small data frame with 6 total variables (x_1 ... x_6). I am trying to plot x_1 against x_2 and x_3. I have tried plot(x_2, x_1) #obviously works fine plot(x_3, x_1, add=TRUE) # Does not work. I keep getting error messages. I would also like to add ablines to this plot. I have experimented with a number of other
2004 May 14
1
help with memory greedy storage
Hello, I've a problem with a self written routine taking a lot of memory (>1.2Gb). Maybe you can suggest some enhancements, I'm pretty sure that my implementation is not optimal ... I'm creating many linear models and store coefficients, anova p-values ... all I need in different lists which are then finally returned in a list (list of lists). The input is a matrix with 84 rows
2009 Nov 12
2
A combinatorial optimization problem: finding the best permutation of a complex vector
Hi, I have a complex-valued vector X in C^n. Given another complex-valued vector Y in C^n, I want to find a permutation of Y, say, Y*, that minimizes ||X - Y*||, the distance between X and Y*. Note that this problem can be trivially solved for "Real" vectors, since real numbers possess the ordering property. Complex numbers, however, do not possess this property. Hence the
1998 Aug 31
0
Packages aov, modreg, lqs, psplines
I now have versions of code that is destined (I believe) for 0.63 which is in a suitable state for comment. The files are at ftp://ftp.stats.ox.ac.uk/pub/R (Our www server is being moved, so may be intermittently down, but this ftp server should be stable.) All are R packages, for the moment for personal use only (no re-distribution). Use with 0.62.3 or 0.63 (although I am aware of some
2012 Dec 18
1
pscore.dist problem when running optmatch
Hello My optmatch package is loaded and otherwise running fine. I get an error after lcds successfully completes logistic regression and I'm trying to obtain a propensity score: > pdist <- pscore.dist(lcds) Error: could not find function "pscore.dist" I searched the help files, other online sources, could find no answer for this. Any advice would be greatly appreciated!
2005 Oct 06
0
a question about LMS and what constitutes outliers
Hi, I have been using the lqs function with method='lms'. However the results I get are a little different from the results noted by Rousseeuw & Leroy (Robust Regression and Outlier Detection) and I was wondering how to use these results for outlier detection. I'm using the stackloss dataset, for which the original Rousseeuw et al. program points out that observations 1,2,3,4
2002 Nov 15
1
Plotting in the margin
Hi, I would like to place a line (tilted at an angle) in the margin of an R plot. Is there any way to place such an annotation outside the plotting area? As an alternative, being able to plot a rotated character (the pipe, |) in the margin would be sufficient. The problem is that mtext doesn't work with the srt option. As a further alternative, if I could put a legend in the margin, I
2007 Oct 04
1
Updating packages for R 2.6.0
Since this has come up already: It is a good idea to re-install all packages for a minor-version increment of R, e.g. 2.5.1 -> 2.6.0 (it is major.minor.patchlevel). This is most easily done by > update.packages(checkBuilt=TRUE, ask=FALSE) However, if you don't want to do that yet, be aware that - Certain S4-using packages must be reinstalled, and using old versions can make R
2003 Dec 03
5
add a point to regression line and cook's distance
Hi, This is more a statistics question rather than R question. But I thought people on this list may have some pointers. MY question is like the following: I would like to have a robust regression line. The data I have are mostly clustered around a small range. So the regression line tend to be influenced strongly by outlier points (with large cook's distance). From the application 's