similar to: Re:Time-Series

Displaying 20 results from an estimated 3000 matches similar to: "Re:Time-Series"

2005 Jan 28
3
GLM fitting
DeaR R-useRs, I'm trying to fit a logist model with these data: > dati y x 1 1 37 2 1 35 3 1 33 4 1 40 5 1 45 6 1 41 7 1 42 8 0 20 9 0 21 10 0 25 11 0 27 12 0 29 13 0 18 I use glm(), having this output: > g<-glm(y~x,family=binomial,data=dati) Warning messages: 1: Algorithm did not converge in: glm.fit(x = X, y = Y, weights = weights, start = start, etastart =
2004 Jul 07
1
Daily time series
Hi, I'm dealing with time series with 1 observaton for day (data sampled daily). I will create a ts object using that time series and the function ts(). In ts() help is written: The value of argument 'frequency' is used when the series is sampled an integral number of times in each unit time interval. For example, one could use a value of '7' for 'frequency' when
2004 Nov 10
1
Loading some function at R startup
Dear R-users, I've built these functions usefell for me to import/export data from/to Excel: importa.da.excel<-function(){read.delim2("clipboard", dec=",") ## questa funzione consente di importare dati da Excel in R ## selezionare in Excel le celle che contengono i dati, ## compresi in nomi delle colonne ## Autore: Vito Ricci email:vito_ricci at yahoo.com ## Data di
2005 Jan 25
1
Fitting distribution with R: a contribute
Dear R-useRs, I've written a contribute (in Italian language) concering fitting distribution with R. I believe it could be usefull for someones. It's available on CRAN web-site: http://cran.r-project.org/doc/contrib/Ricci-distribuzioni.pdf Here's the abstract: This paper deals with distribution fitting using R environment for statistical computing. It treats briefly some
2004 Oct 22
3
Convert a list in a dataframe
Hi, I've a list containing parameters (intercepts & coefficients) of 12 regressions fitted > coeff [[1]] (Intercept) anno -427017.1740 217.0588 [[2]] (Intercept) anno -39625.82146 21.78025 ..... [[12]] (Intercept) anno 257605.0343 -129.7646 I want create a data frame with two columns (intercept and anno)using data in these list. Any help
2005 Jul 08
1
Orthogonal regression
Dear R-Users, is there any statement to fit a orthogonal regression in R environment? Many thanks in advance. Best regards, Vito Diventare costruttori di soluzioni Became solutions' constructors "The business of the statistician is to catalyze the scientific learning process." George E. P. Box "Statistical thinking will one day be as necessary for efficient
2004 Nov 22
1
R: simulation of Gumbel copulas
Hi, I found this document, but it concerns S+. If it could interest you'll see: http://faculty.washington.edu/ezivot/book/QuanCopula.pdf Cordially Vito You wrote: Dear R: Is there a function or a reference to simulate Gumbel copulas, please? Thanks in advance! Sincerely, Erin Hodgess mailto: hodgess at gator.uhd.edu R version 2.0.1 windows ===== Diventare costruttori di soluzioni
2005 Jan 13
2
chisq.test() as a goodness of fit test
Dear R-Users, How can I use chisq.test() as a goodness of fit test? Reading man-page I?ve some doubts that kind of test is available with this statement. Am I wrong? X2=sum((O-E)^2)/E) O=empirical frequencies E=expected freq. calculated with the model (such as normal distribution) See: http://www.itl.nist.gov/div898/handbook/eda/section3/eda35f.htm for X2 used as a goodness of fit test. Any
2004 Jul 21
2
Testing autocorrelation & heteroskedasticity of residuals in ts
Hi, I'm dealing with time series. I usually use stl() to estimate trend, stagionality and residuals. I test for normality of residuals using shapiro.test(), but I can't test for autocorrelation and heteroskedasticity. Is there a way to perform Durbin-Watson test and Breusch-Pagan test (or other simalar tests) for time series? I find dwtest() and bptest() in the package lmtest, but it
2004 Oct 27
2
Skewness and Kurtosis
Hi, in which R-package I could find skewness and kurtosis measures for a distribution? I built some functions: gamma1<-function(x) { m=mean(x) n=length(x) s=sqrt(var(x)) m3=sum((x-m)^3)/n g1=m3/(s^3) return(g1) } skewness<-function(x) { m=mean(x) me=median(x) s=sqrt(var(x)) sk=(m-me)/s return(sk) } bowley<-function(x) { q<-as.vector(quantile(x,prob=c(.25,.50,.75)))
2004 Oct 20
2
R & Graphs
Dear R-users, I'm finding for a R-package concerning graphs. Is there some kind of that package? I've a set of correlation coeffients between several variable and I wish to built a graph to link variables correlated. Many thanks. Best, Vito ===== Diventare costruttori di soluzioni "The business of the statistician is to catalyze the scientific learning process." George
2004 Nov 15
1
R: how can draw probability density plot?
I hope this example could help you best vito > x<-seq(-3.5,3.5,0.1) > x [1] -3.5 -3.4 -3.3 -3.2 -3.1 -3.0 -2.9 -2.8 -2.7 -2.6 -2.5 -2.4 -2.3 -2.2 -2.1 [16] -2.0 -1.9 -1.8 -1.7 -1.6 -1.5 -1.4 -1.3 -1.2 -1.1 -1.0 -0.9 -0.8 -0.7 -0.6 [31] -0.5 -0.4 -0.3 -0.2 -0.1 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 [46] 1.0 1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9 2.0 2.1 2.2 2.3
2004 Dec 02
1
Re: A somewhat off the line question to a log normal distribution
Dear Siegfried, I believe your boss is wrong saying that: >He also tried to explain me that the monthly means >(based on the daily measurements) must follow a >log-normal distribution too then over the course of a year. every statistician know that increasing the sample size the sample distribution of the mean is proxy to a gaussian distribution (Central Limit Theorem) independently
2004 Nov 12
4
Mode in case of discrete or categorial data
Thanking John for his suggestion I build this function which get the mode of both categorial and discrete data. Mode<-function(x){t<-table(x) if (is.numeric(x)) as.numeric(names(t)[t == max(t)]) else (names(t)[t == max(t)]) } Any other improvement and suggestion will welcome. Best Vito > s [1] 1 1 6 1 1 7 6 5 6 2 1 4 5 6 6 7 3 5 4 1 7 3 7 3 3 7 7 2 1 4 4 2 7 7 6 6 1 2 [39] 5 1 7 7
2004 Nov 17
1
R: log-normal distribution and shapiro test
Hi, from what you're writing: "The logaritmic transformation "shapiro.test(log10(y))" says: W=0.9773, p-value= 2.512e-05." it seems the log-values are not distributed normally and so original data are not distributed like a log-normal: the p-value is extremally small! Other tests for normality are available in package: nortest compare the log-transformation of your ecdf
2005 Jan 11
3
Kolmogorov-Smirnof test for lognormal distribution with estimated parameters
Hello all, Would somebody be kind enough to show me how to do a KS test in R for a lognormal distribution with ESTIMATED parameters. The R function ks.test()says "the parameters specified must be prespecified and not estimated from the data" Is there a way to correct this when one uses estimated data? Regards, Kwabena. -------------------------------------------- Kwabena Adusei-Poku
2004 Aug 09
2
Using R "boxplot" function in Excel
Hi, I have downloaded the "R-Com and I was able to run "Interactive Graphics Demo 2" in excel. However, I couldn't create my own boxplot. Whenever I tried to run any code, it always say" Error in loading DLL", even "=rput(A1,A2:A20)". Any idea about what's going wrong? A detailed explaination about how to use R-Excel tool would be greatly appreciated.
2005 Feb 07
0
R: Creating a correlation Matrix
Hi, see ?cor in base package to get correlation matrix for your data. Maybe it could be usefull getting principal components (give a look to: ? princomp (base)) to reduce the number of variables. Hoping I helped you. Best regards, Vito You wrote: Hi all: I have a question on how to go about creating a correlation matrix. I have a huge amount of data....21 variables for 3471 times. I want
2004 Dec 03
0
R: vector to matrix transformation
Hi, did you see: as.data.frame() as.matrix() as.vector() matrix() > x a b c 1 1 2 3 2 1 2 3 3 2 3 4 4 3 4 5 > is.data.frame(x) [1] TRUE > as.matrix(x) a b c 1 1 2 3 2 1 2 3 3 2 3 4 4 3 4 5 > y<-as.matrix(x) > is.matrix(y) [1] TRUE > as.vector(y) [1] 1 1 2 3 2 2 3 4 3 3 4 5 > z<-as.vector(y) > m<-matrix(z,ncol=3) > m [,1] [,2] [,3] [1,] 1 2
2005 Jan 20
0
Re: suggestion on data mining book using R
Hi, see these links: http://www.liacc.up.pt/~ltorgo/DataMiningWithR/ http://sawww.epfl.ch/SIC/SA/publications/FI01/fi-sp-1/sp-1-page45.html Brian D. Ripley, Datamining: Large Databases and Methods, in Proceedings of "useR! 2004 - The R User Conference", may 2004 http://www.ci.tuwien.ac.at/Conferences/useR-2004/Keynotes/Ripley.pdf looking for a book I suggest: Trevor Hastie , Robert