similar to: Need R Version 1.8.0 or earlier

Hello, R users, I am a very beginner of R and tried read.csv to import an excel file after saving an excel file as csv. But it added alternating rows of fictitious NA values after row number 16. When I applied read.delim, there were trailing several commas at the end of each row after row number 16 instead of NA values. Appreciate your help. Kyong [[alternative HTML version deleted]]

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

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.

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

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)))

I would be very grateful for any help from members of this list for what might be a simple problem... We are trying to simulate the behaviour of a clinical measurement in a series of computer experiments. This is simple enough to do in R if we assume the measurements to be Gaussian, but their empirical distribution has a much higher peak at the mean and the distribution has much longer tails.

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

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

Hi, How do I open an excel file in R? I have save the excel file in unicode text format, but it is not possible to open the file in R. /Pernilla

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

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

Is there a method that converts a csv file to a data frame ? M

Hi, Is there any package or functions in R that can perform tests and estimation for a spatial econometric model in a simultaneous system? Thank you!!! Xia Feng

Hi, Not sure if I am making a simple problem complex but still here we go: I have a data frame with four columns say, X1 X2 X3 and X4. I want to break X4 into deciles and for each deciles obtained, I want to see corresponding elements of X1. Ideally, the output should be in a tabular fashion as shown below: Deciles 1 Deciles 2 .... Deciles 10 X1-1 X1-2 X1-99 X1-5 X1-3 X1-10

I would be grateful if members of the list could point me in the direction of any code (preferably in R) that will allow me to estimate 95th percentiles from a set of repeated measurements. For example, we are interested in a clinical measurement where we have 3 measures for 14 subjects and 2 measurements on 24 subjects and single measurement on 36 subjects. We want to combine these to form a

Hi, Why this code is good in S-plus, and don't good in R ? getMethod("[","matrix") thanks

Bonjour, Je veux cherché l’estimateur de vraisemblance maximal (MLE)d’une fonction à 3 paramètre inconue étant donné une échantillon de taille 50 (les observations des valeurs de x) alors comment je peux procédé La fonction de densité est définie par : f(x)= 1/3(g(a1)+g(a2)+g(a3)) avec g(ai)=(exp(ai)*ai^x)/x! pour i=1,2,3. Je vous remercie beaucoup. A. Elhabti

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

Hello! I have a continous distribution and would like to get mode (the most frequent value in distribution). I easily found mean, median and other basic thing but not mode function. Can anyone help? I know there my might be problems with multiple modes, but still I think that there should be a mode function in R. Please send mail to R-help list and me, so I can get response faster. Thank

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