similar to: ratios

i read about the performance analytics package i have a doubt about the TreynorRatio i have code g=getSymbols("IBM") > c=Cl(g) > r=Return.calculate(c) > SharpeRatio.annualized(r) IBM.Close Annualized Sharpe Ratio (Rf=0%) 0.3566339 > TreynorRatio (ret) Error in inherits(x, "xts") : argument "Rb" is missing, with

i need to find the best ticker from the group of some tickers.? i also need to know on what basis we calculate the best ticker? i have some idea about the if the risk rate low, or the market price high we can say the ticker is best. but i dont know is it true. Anyone can help me . Thank you -- View this message in context:

How to call a function from another r file ? Anyone can help me . Having a function named like fun1 which is saved in r file file1.r and i have another r file like file2.r, and i need to call the fun1 (which is in file1) within file2. Thank you -- View this message in context: http://r.789695.n4.nabble.com/function-call-from-another-r-file-tp4650627.html Sent from the R help mailing list

All, I'm attempting to run this: table.CAPM(series[,"Strat.Return",drop=FALSE],series[,"spy.Return",drop=FALSE]) and getting this error Error in as.vector(data[, i]) : subscript out of bounds I've searched around and cannot find a solution to the problem.  I've used this in the past without problem and I'm not sure what I did different this time. Other

In performance analytics - performance summary session , i cant run the code of - charts.PerformanceSummary(datafrom_table, rf = 0, main = NULL, method = "ModifiedVaR", width = 0,event.labels = NULL, ylog = FALSE, wealth.index = FALSE, gap = 12) it just return blank chart. datafrom_table - having a csv file. and the rest of the things are get from the site

I am a new R user (am using it through the Rcmdr package) and have struggled to find out how to report OR and RR directly when running GLM models (not only reporting coefficients.) Example of the syntax that I have used: GLM.2 <- glm(diarsev ~ treatmentarm +childage +breastfed, family=binomial(logit), data=fieldtrials2) summary(GLM.2) This works well except that I manually have to calculate

Dear R-users: How does one calculate in R the odds ratios for a CATEGORICAL predictor variable that has 4 levels. I see r-help inquiries regarding odds ratios for what looked like a continuous predictor variable. I was wondering how to get the pairwise odds ratios for comparisons of levels of a categorical predictor variable. I can't seem to get the correct output using: >

Hi there, is there any way to compare 2 odds ratios? I have two tests that are supposed to detect a disease presence. So for each test, I can compute an odds ratio. My problem is how can I compare the 2 tests by testing whether the 2 odds ratios are the same? Appreciate

Does anyone know of another version of the Mcnemar test that provides: 1. Odds Ratios 2. 95% Confidence intervals of the Odds Ratios 3. Sample probability 4. 95% Confidence intervals of the sample probability Obviously the Odds Ratios and Sample probabilities are easy to calculate from the contingency table, but I would appreciate any help on how to calculate the confidence

The code library(Design) f <- lrm(y~x1+x2+x1*x2, data=data) plot(f) produces a plot of log odds vs x2 with 0.95 confidence intervals. How do I get a plot of odds ratios vs x2 instead? Thanks -- View this message in context: http://r.789695.n4.nabble.com/Odds-ratios-from-lrm-plot-tp4033340p4033340.html Sent from the R help mailing list archive at Nabble.com.

Hi, I'm using the rms package to do regression analysis using the lrm function. Retrieving odds ratios is possible using summary.rms. However, I could not find any information on how exactly the odds ratios for continuous variables are calculated. It doesn't appear to be the odds ratio at 1 unit increase, because the output of summary.rms did not match the coefficient's value. E.g.

hi Michael, am sorry for the incomplete reply . csv file data havinmg like this , >getSymbols("IBM") >weekly_data = to.weekly(week_name) >dataframe=data.frame(weekly_data) >outputfile_name="F:\\R-programs\\Outputfile.csv" >write.table(dataframe, file =outputfile_name,sep = ",",col.names =TRUE,row.names = T) > datafrom_table <-

I am trying to do logistic regression with a categorical predictor variable with the glm() function, family=binomial. Using glm() I would like to be able to calculate the confidence intervals of all three possible odds ratios for a factor (the factor has three categories). Three categories imply two columns of 0's and 1's in the design matrix, and two parameter estimates with their

I have a data matrix with genes as columns and samples as rows. I want to create all possible gene ratios.Is there an elegant and fast way to do it in R and write it to a dataframe? Thanks for any help. Som. -- View this message in context: http://r.789695.n4.nabble.com/Calculating-all-possible-ratios-tp4627405.html Sent from the R help mailing list archive at Nabble.com. [[alternative HTML

I'm looking for a way to generalize the calculation of (log) odds ratios for 2 x 2 x {strata} frequency tables in vcd::oddsratio() to R x C x {strata} tables. For an R x C table, F, odds ratios can be defined in several ways; one simple way, particularly for tables with ordered factors, is to calculate the set of continuation odds ratios, based on the (R-1)x(C-1) set of 2x2 tables with

Hi folks, I have assumed that ratios of variance components (Fst and Qst in population genetics) could be estimated using the output of mcmcsamp (the series on mcmc sample estimates of variance components). What I have started to do is to use the matrix output that included the log(variances), exponentiate, calculate the relevant ratio, and apply either quantile or or HPDinterval to get

Dear useRs, I have two different length vectors: one column (1...m) and one row vector (1...n): 20 40 20 60 5 4 2 Now I have to calculate ratios between column vector elements and each row vector elements: 4 5 10 8 10 20 4 5 20 15 12 30 Thank's in advance for any suggestions, Andrej

Hi, I am trying to calculate the std dev of returns of YHOO so far i got: getSymbols("YHOO") retYHOO <- Return.calculate(Cl(YHOO)) > sd(retYHOO) YHOO.Close NA but i received an NA....can any assist? tks! -- View this message in context: http://www.nabble.com/Newbie-question-re-stddev%2C-quantmod-and-performanceanalytics-tp25001293p25001293.html Sent from the R help

Greetings, I am new to R and have been comparing CPH survival analysis hazard ratios between R and SAS PhReg. The binary covariates' HRs are the same, however the continuous variables, for example age, have quite different HRs although in the same direction. SAS PhReg produces HRs which are the change in risk for every one increment change in the independent variable. How do I

so here is the code I need help to fix the line for 'st' when it reaches maximum, that's where i am getting stuck. thanks Sharad set.seed(100) d=data.frame(x=rnorm(20)+5, x1=rnorm(20)+5, x2=rnorm(20)+5, x3=rnorm(20)+5, x4=rnorm(20)+5, x5=rnorm(20)+5, x6=rnorm(20)+5, x7=rnorm(20)+5, x8=rnorm(20)+5) r2=c() cinit=0 for (col in 1:9) { cinit=cinit+1 st=cinit+1