similar to: How can I interpret this test hypothesis test

Hi wizards, I have seen the function svd of R for singular value decomposition, but I need to computes the ``economy size'' or ``thin'' singular value decomposition of a matrix in R. Somebody knows how to do that?. Thanks in advance. -- Web Page http://geocities.com/lord_tyranus_96/

-----BEGIN PGP SIGNED MESSAGE----- Hash: SHA1 First of all, I'm a physicist and therefore I'm not much used to use statistics. So, please forgive me if this is a FAQ or stupid, but I failed to find the answer by myself. I want to use corr.test to test for the correlation of two data sets (actually I have a lot of data set and perform pairwise testing). But I wanted to find sets where the

Dear all- Package /fGarch/ version 2100.78 in R version 2.8.1 (2008-12-22) running on linux 2.6.22.9-91.fc7 In trying to fit garch models in above environment. I am getting "reasonable" fitted coefficients, but the fitObject@fitted are all the same. This is true even for the help page example: library(fGarch) R> X.timeSeries = as.timeSeries(msft.dat) R> head( +

Dear R-users, Is there a way to get p-values for a one-sided hypothesis test about a poisson mean? Thanks, Jan Wijffels University Center for Statistics W. de Croylaan 54 3001 Heverlee Belgium tel: +32 (0)16 322784 fax: +32 (0)16 322831 <http://www.kuleuven.be/ucs> http://www.kuleuven.be/ucs Disclaimer: http://www.kuleuven.be/cwis/email_disclaimer.htm [[alternative HTML version

This was sent to me by someone on the R-list ( I don't know her ) but I don't have time to look at this right now so I told her I would send it to the R-list because she said it keeps getting bounced when she sends it. #======================================================================= ==================================================================== I am a bit confused with

I've just discovered R and think it is terrific. I quickly reproduced results with a few lines of R commands that 7 years ago I had to do with a larger fortran code and many calls to NAG routines. (I'm mostly a computational plasma physicist, but occasionally delve into statistical analysis of data.) But I've come accross a very peculiar behavior of attached objects that cost me

Dear R-help, I am interested in using structural equation modeling. Just getting started with it, but I'm looking for suggestions for packages. As an aside, what's the best way for looking for packages at CRAN? -- Robert Terwilliger Biomedical Physicist Laboratory of Neurocognitive Development Western Psychiatric Institute and Clinic University of Pittsburgh Medical Center Loeffler

Dear R users I am using KS test to compare two different distribution for the same variable (temperature) for two different time periods. H0: the two distributions are equal H1: the two distributions are different ks.test (temp12, temp22) Two-sample Kolmogorov-Smirnov test data: temp12 and temp22 D = 0.2047, p-value < 2.2e-16 alternative hypothesis: two-sided Warning message: In

hi, i am trying to teach myself about ARIMA models. i have followed examples from a number of sources and have more or less got the hang of how it works. i would like to compare the output from the fitted model to the original data. is this possible? or even a meaningful thing to do? to be clear, for example, having generated a fit to some data using > fit <- arima(LakeHuron, order = c(1,

I have some data consisting of multiple trials of an experiment with different values of an independent variable. If I run R> plot(var,result) I get a scatterplot of result versus the independent variable var. If I run R> plot(as.factor(var),result) I get a boxplot of the distribution of result for each value of var. In this plot, each boxplot is labeled by the corresponding value of

Hi With ggplot2 I can very easily create beautiful histograms but I would like to put two histograms on the same plot. The histograms may be over-lapping. When they are overlapping the bars are shown on top of each other (so that the overall height is the sum of the two). Is there any way to get them to display overlapping (with smaller value in front, larger value behind) so that the overall

Hi, Interpretation problem ! so what i did is by using the: >fit1 <- fitdist(vectNorm,"beta") Warning messages: 1: In dbeta(x, shape1, shape2, log) : NaNs produced 2: In dbeta(x, shape1, shape2, log) : NaNs produced 3: In dbeta(x, shape1, shape2, log) : NaNs produced 4: In dbeta(x, shape1, shape2, log) : NaNs produced 5: In dbeta(x, shape1, shape2, log) : NaNs produced 6: In

hi, i am sure that this is a trivial question but i have not been able to find an answer by searching the mailing lists. i want to plot points on a graph, joined by lines. the command that i am using is points(x, y, type = "b", pch = 21) this plots nice open circles at the data points and draws lines between them. however, the lines do not come all the way up to the edge of the

I''m a physicist working on fusion energy and dabble in statistics only occasionally, so please excuse gaps in my statistical knowledge. I''d appreciate any help that a real statistics expert could provide. Most people in my field do only very simple statistics, and I am trying to extend some work on multivariate linear regression to account for significant between-group

Hi I have a long data set on which I want to do Bland-Altman style plots for each rhythm type Using ggplot2, when I use geom_hline with facet_grid I get an extra set of empty panels. I can't get it to do it with the "Diamonds" data supplied with the package so here is a (much abbreviated) example: > lvexs cvd_basestudy ecd_rhythm fixed_time variable_time 1 CBP05J02

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# Hi all: #I got a vector with fish lengths(mm) # Can someone help me interpret the output of # a t.test in plain english? # Based on the t.test below I can say that # I reject the null hypothesis because # the p-value is smaller than the the significance # level(alpha=0.05). What else can I conclude here? Ho = 36 mm Ha <> 36 mm fishlength

DeaR list, Has anyone tried to mix the Sweave paradigm with the Markdown[*] (and co.) syntax? Would this be hard to implement? My tiny understanding of Sweave is that one can define new drivers for the text part, while some functions that deal with the R code would not require any modification. Here's the reason I'm interested in Mardown for a driver. I've been orbiting

Dear All- I am looking at the bivariate point process model for extreme values as described in Section 8.3.2 of Coles book. I am stuck at a very low level in being unable to reproduce the initial step of transforming the data to unit Frechet margins. In particular, I am unable to reproduce the wave-surge pairs distribution after transformation to Frechet scale (Figure 8.6 of Coles

Hello all, Do you know of convenient functions that can do: 1) a fit "f(x)" of data points with a spline, and *then* 2) weighted fits of other data points ** with a model of the form a*f(x-x0)?**? [i.e., the goal is to find a and x0, ideally with their covariance matrix], and 3) if possible, the same as (2) above, but with the same model *convoluted with a gaussian* (whose