similar to: time series regression

Hi: I have two vectors of data, x and y and I want to get the "polynomial" expansion of (x+y)^p with any integer power p in R. Suppose p=2, then I want a matrix of five vectors, namely, x y x^2 y^2 x*y. The coefficient of the polynomial is not needed. I can write it manully if p is small. But I want it in the case of p=10 or even bigger, is there any function in R can do that

Hi: I have some problems when I use the function "solve" function in a loop. In the following code, I have a diagonal martix "ttt" whose elements change in every iteration in a loop. I defined a "dpoMatrix"class before the loop so I do not need to define this class every time in the loop. The reason is to save some computing time. The code is below. The inverse

Hi: I used the function "lme" in R and Splus-7. With the same dataset and same argument for the function, I got quite different estimation results from these two software. Anyone has this experience before? zhong --------------------------------- Get your own web address. [[alternative HTML version deleted]]

Hi: Is there any function in R which can convert the long/lat to UTM(Universal Transverse Mercator)? There are quite a few converters on Internet. However, the interface is designed as input->output which I can not convert lots of locations at the same time. Another question is whether there is a function in R which can tell the time zone from the location's lat/long? Thank you!

Hi: I am doing a MCMC algorithm which is well known to consume much computer memory. And I have a problem everytime I run my R program. It stopped at certain iteration and says "can not allocate a vector of 19 kb". It seems that the computer's memory has been exhausted. However, it is said that after each iteration the objects (such as a huge matrix) can be set to NULL. And the

Hi: I have a data file in the following format. The first three digits stand for the ID of a respondent such as 402, 403. Different respondents may have the same ID. Followed the ID are 298 single digit number ranging from 1 to 5. My question is how to read this data file into R. I tried "scan" and "read" but they do not work because the numbers in the file are not

Hello, I am attending a course in Computational Statistics at ETH and in one of the assignments I am asked to prove that a time series is not autocorrelated using the R function "acf". I tried out the acf function with the given data, according to what I found here: http://landshape.org/enm/options-for-acf-in-r/ this test data does not look IID but rather shows some trends so how can I

Hi: The gls function I used in my code is the following fm<-gls(y~x,correlation=corARMA(p=2) ) My question is how to extact the AR(2) parameters from "fm". The object "fm" is the following. How can I extract the correlation parameters Phi1 and Phi2 from "fm"? These two parametrs is not in the "coef" componenet of "fm". Thanks a

Hi: I followed the README in src/nmath/standalone/ to make the use the command "make shared" to make the libRmath.so file. I also add the directories containg libRmath.so to LD_LIBRARY_PATH by using command "export D_LIBRARY_PATH=$LD_LIBRARY_PATH:$/home/zhliu/Backup/R-2.0.1/src/nmath/standalon e " However, when I try to run the following codes by the command

Dear list, After running for a while, it crashes and gives the following error message: can anybody suggest how to deal with this? Error in if (ratio0[i] < log(runif(1))) { : missing value where TRUE/FALSE needed ################### original program ######## p2 <- function (Nsim=1000){ x<- c(0.301,0,-0.301,-0.602,-0.903,-1.208, -1.309,-1.807,-2.108,-2.71) # logdose

Dear R community: I am trying to do a simulation study mentioned by Fu (1998), Journal of Computational and Graphical Statistics, Volume7, Number 3, Page 397-416. In order to give a clear statement of quesion I copy the following paragraph from the article: We compare the bridge model with the OLS, the lasso and the ridge in a simulation of a linear regression model of 30 observations and 10

hello R experts, my question is regarding arma modelling and specification. in another older, statistics package , after determining stationarity, i would try to work out the number of ar and ma lags using an lm test. to do this i would 1. regress my dependant variable on an intercept term then 2. use LM test for serial correlation, and finally 3. use the p value of the ols residuals to get

Hi, how to estimate a the following model in R: y(t)=beta0+beta1*x1(t)+beta2*x2(t)+...+beta5*x5(t)+beta6*y(t-1)+beta7*y(t-2)+beta8*y(t-3) 1) using "lm" : dates &lt;- as.Date(data.df[,1]) selection&lt;-which(dates&gt;=as.Date("1986-1-1") &amp; dates&lt;=as.Date("2007-12-31")) dep &lt;- ts(data.df[selection,c("dep")]) indep.ret1

Hi, can anyone help me fit betabinomial model to the following dataset where each iD is a cluster in itself , if i use package aod 's betabinom model it gives an estimate of zero to phi(the correlation coeficient ) and if i fix it to the anova type estimate obtained from icc( in package aod) then it says system is exactly singular. And when i try to fit my loglikelihood by

Hi, I'm trying to get maximum likelihood estimates of \alpha, \beta_0 and \beta_1, this can be achieved by solving the following three equations: n / \alpha + \sum\limits_{i=1}^{n} ln(\psihat(i)) - \sum\limits_{i=1}^{n} ( ln(x_i + \psihat(i)) ) = 0 \alpha \sum\limits_{i=1}^{n} 1/(psihat(i)) - (\alpha+1) \sum\limits_{i=1}^{n} ( 1 / (x_i + \psihat(i)) ) = 0 \alpha \sum\limits_{i=1}^{n} (

Hi I have some panel data for the 50 US states over about 25 years, and I would like to test a simple model via OLS, using this data. I know how to run OLS in R, and I think I can see how to create Panel Corrected Standard Errors using http://jackman.stanford.edu/classes/350C/pcse.r What I can't figure out is how to correct for autocorrelation over time. I have found a lot of R stuff on

Hi there, I am using gls from the nlme library to fit an AR(1) regression model. I am wondering if (and how) I can separate the auto-correlated and random components of the residuals? Id like to be able to plot the fitted values + the autocorrelated error (i.e. phi * resid(t-1)), to compare with the observed values. I am also wondering how I might go about calculating confidence (or

Greetings. There seems to be a problem with the P-value computation in the cor.test with method="spearman". In R1.8.0 (MS Windows) I seem to be getting intermittently nonsense P-values, but the rho's are OK. I can get this reproducibly with the toy example attached where the first use is OK and subsequent calls with the same data give nonsense. (I have also seen the problem

HI >i have a little problem please help me to solve it >this is the code in R: >> beta0 [1] 64.90614 > beta1 [1] 17.7025 > beta [1] 17 64 >her beta<- c(beta0, beta1) thank you in advance hafida -- View this message in context: http://r.789695.n4.nabble.com/Decimal-number-tp4639428.html Sent from the R help mailing list archive at Nabble.com.

Dear Users, I am new to both of things, so do not blame me too much... I am busy with semiparametric regression and use WinBUGS to sample posteriors. The code to call Winbugs is as follows: data <- list("y","X","n","m") #My variables inits.beta <- rep(0,K) inits.beta0 <- 0 inits <-