similar to: Parse Expression

Hello everyone, I get some data in the following format and I would like to combine them to form a dataframe. The data is like: cbcname1 = 0.1, cbcname2= 0.2, cbcname3=0.3,... name1, name2, name2 are just some random names. I would like to achieve sth like: (cbcname1=0.1, cbcname2=0.2, cbcname3=0.3,......) I am using the following codes do.call(cbind,

Hello, I define a dataframe named "Price" first and there are other dataframes as well. Then I built an array named "code" containing all the dataframe name. So If I call code[1], it is "Price". Basicly, I would like to call the datafram with reference to the array"code".e,g, If I want to call dataframe "Prices", I use sth containing code[1]. It

Hi All, I am trying to make a loop for a function and I am using the following codes. "p" and "var" are some matrix obtained before. I would like to apply the function "gpdlow" for i in 1:12 and get the "returnlow" for i in 1:12. But when I ask for "returnlow" there are warnings and it turns out some strange result. for (i in 1:12){ gpdlow

Hello, I would like to fit a linear regression and when I use summary(), I got the following result: Call: lm(formula = weight ~ group - 1) Residuals: Min 1Q Median 3Q Max -1.0710 -0.4938 0.0685 0.2462 1.3690 Coefficients: Estimate Std. Error t value Pr(>|t|) groupCtl 5.0320 0.2202 22.85 9.55e-15 *** groupTrt 4.6610 0.2202 21.16 3.62e-14

Hello, I am using the following codes to plot a histogram and density line for x. For the density line, I just want it to show the two tails, eg, for x larger than 0.05 ans smaller than -0.05 hist (x, seq(-0.1,0.1,0.01),freq = FALSE) lines (density(x,bw="SJ"), x> 0.05 & x< (-0.05), col = "red") But is does not work, can anyone give me some advice? -- View this

Hello, I would like to perform a linear regression and the data is a list.e.g lm(list$abc~., data=list) or lm(abc~., data=list), which would give the same result. The problem is I would like to call the response variable in a more general form. What I try to achieve is sth like lm(list$(paste("a","b","c"))~., data=list), but it does not work. Could anyone give me

Hi, I would like to generate a series in the following form (0.8^1, 0.8^2, ..., 0.8^600) Could anyone tell me how can I achieve that? I am really new to R. -- View this message in context: http://www.nabble.com/sequences-tf4019146.html#a11414836 Sent from the R help mailing list archive at Nabble.com.

Hi, I am trying to write a function with the following codes and I would like it to return the values for "alpha beta para parab " seperately. Then I would like to use this funstion for "variable" with factor "a" and "b". But the result turns out to be a matrix with element like "Numeric,2" ... I guess they are just the values for

Hello all, I would like to plot the emperical CDF, normal CDF and pareto CDF in the same graph and I amusing the following codes. "z" is a vector and I just need the part when z between 1.6 and 3. plot(ecdf(z), do.points=FALSE, verticals=TRUE, xlim=c(1.6,3),ylim=c(1-sum(z>1.6)/length(z), 1)) x <- seq(1.6, 3, 0.1) lines(x,pgpd(x, 1.544,0.4373,-0.2398), col="red") y

Hi, I have a series of return data, a and b are factors. I would like to build a matrix which contains each vector of "returns". I am thinking about something as following, but I guess there should be a sensible way of doing this. returns <- split(return, list(regimef, assetf)) cbind(returns[[1]], returns[[2]],...,returns[[n]]) Could anyone give me some advice? Many thanks. --

I have got a list named "filtered", I would like to construct alist named "fdata" as following: fdata <- cbind(matrix(unlist(filtered),ncol=28), myregime) If I try names(filtered), it gives all the correct name for each vector, but if I try names(fdata), it appears "filtered[[1]]" "filtered[[2]]" ..., How can I keep the name in "fdata"?

Hello, I would like to use the cbind() function to construct a matrix used in the middle of a function as following for (i in 1:1000) { b[i] <- function(cbind(a[[1]][[i]], a[[2]][[i]],a[[3]][[i]],...a[[67]][[i]])) } Is there an easy way of achieving this rather than "cbind" every column? -- View this message in context: http://www.nabble.com/cbind%28%29-tf4724534.html#a13507633

Hello everyone, I would like to a linear regression with the following code. lm(a[,"fquamsci"]~., data=a) a is a list with class "mts" "ts" , and "fquamsci" is the name of the response variable in a. I would like to do a linear regression of "fquamsci" to the rest of the variables. But it turns out the "fquamsci" is also included in

Hi, I want to import some data from Access and I am using the following codes: testdb <- file.path("c/../db1") channel <- odbcConnect("testdb") sqlFetch(channel,"tbl",colnames = TRUE, rownames = FALSE) It comes out the error message: 1: [RODBC] ERROR: state IM002, code 0, message [Microsoft][ODBC Driver Manager] Data source name not found and no default

Hello, I want to conduct normality test to a series of data and get the p-value for each subset. I am using the following codes, but it does not work. tapply(re, list(reg, ast), pvalue(shapiro.test)) Could anyone give me some advice? Many thanks. -- View this message in context: http://www.nabble.com/tapply-tf3851631.html#a10910748 Sent from the R help mailing list archive at Nabble.com.

I would like to fit a Pareto Distribution and I am using the following codes fit=vglm(ycf1 ~ 1, pareto1(location=alpha), trace=TRUE, crit="c") fitted(fit) But the fitted values turn out to be the same for each observation. I guess the problem is with "ycf1 ~ 1", I would be grateful if anyone can give me some advice on how to define the formula. Many thanks -- View this

Hello, I would like to use the Exponential Weighted Moving Average procedure to get the variance. Is there any R function for doing this? Many thanks. -- View this message in context: http://www.nabble.com/EWMA-procedure-to-forecast-variance-tf4018317.html#a11412324 Sent from the R help mailing list archive at Nabble.com.

Hi all, I am trying to fit t distribution using the function "tFit" in the library(fBasics). I am using the code tFit(datac[[2]]) and it returns the following list. Title: Student-t Parameter Estimation Call: tFit(x = datac[[2]]) Model: Student-t Distribution Estimated Parameter(s): df 78.4428 I just wonder how can I refer to the estimated parameters. I tried

Hello everyone, I would like to use the "cbind" function to construct a dataset, combining some variable I defined before. The codes are something like var1 <- ... var2 <- ... var2 <- ... ... data <- cbind(var1,var2,var3...) The problem is I would like some flexibity in the data, i.e. the number of the variables are not fixed. Is there a method of combine the uncertain

PREFERED WAY OF DOING IT I have a data set of observations every second for a month long period, I want to extract the observations according to the date & time of another data frame ( the other data frame is in the same format). I want to do this to match these observations to my test observations (in the other data frame) which are done every 6 minutes. So basically im shrinking the