similar to: Patch for format.pval limitation in format.R

'format.pval' has a major limitation in its implementation for example suppose a person had a vector like 'a' and the error being ?0.001. > a <- c(0.1, 0.3, 0.4, 0.5, 0.3, 0.0001) > format.pval(a, eps=0.001) The person wants to have the 'format.pval' output with 2 digits always showing like this [1] "0.10" "0.30"

Full_Name: Charles Dupont Version: 2.4.1 OS: linux 2.6.18 Submission from: (NULL) (160.129.129.136) 'format.pval' has a major limitation in its implementation. For example suppose a person had a vector like 'a' and the error being ?0.001. > a <- c(0.1, 0.3, 0.4, 0.5, 0.3, 0.0001) > format.pval(a, eps=0.01) If that person wants to have the 'format.pval'

Hi List, My goal is to force R not to print in scientific notation in the sixth column (rel_diff - for the p-value) of my data frame (not a matrix). I have used the format.pval () and printCoefmat () functions on the data frame. The R script is appended below. This issue is that use of the format.pval () and printCoefmat () functions on the data frame gives me the desired results, but coerces

Today I stumbled upon a very strange behaviour of format.pval. If all p values are below the threshold eps one gets format.pval(c(0.0002, 0.0004), eps = 0.001) ## [1] "< 0.001" "< 0.001" format.pval(0.0004, eps = 0.001) ## [1] "< 0.001" i.e., "< [eps]" as described in the manual of format.eps. Yet, if one ore more are above (and one or more

I can reproduce this. It has to do with whether the value rounds down to 9 or up to 10, and thus needs another space, I think. I agree that it shouldn't happen, but at least you can get rid of the space by using trim = TRUE. # rounds to 9 vs 10 format(9.95, digits = 2) format(9.96, digits = 2) format(9.95, digits = 2, nsmall = 2) format(9.96, digits = 2, nsmall = 2) format(9.95, digits =

>From the help page of format, nsmall should control the number of digits. > format(0.123456789, nsmall = 10) [1] "0.1234567890" > format(0.123456789, nsmall = 1) [1] "0.1234568" > format(0.123456789, nsmall = 2) [1] "0.1234568" > format(0.123456789, nsmall = 8) [1] "0.12345679" It adds zeros fine but for

Dear Dr. Graves Many thanks for your response. FDRs and their associated q values do differ from Type I error rates and P values (See Storey and Tibshirani PNAS 2003;100:9440-5). It is an approach that is rapidly gaining popularity in the analysis of genomic data where we have massive numbers of covariates measured on a comparatively modest number of subjects. To my mind it is a real advance

Full_Name: Dirk Jacob Version: R 2.8.1 and 2.9.1 OS: Win XP Submission from: (NULL) (153.96.32.62) I want to convert numbers to strings like: > inputs= c(0.3+0*(1:12) ) > (format(inputs,digits=3,scientific=T,collapse=" ")) and it works [1] "3e-01" "3e-01" "3e-01" "3e-01" "3e-01" "3e-01" "3e-01"

Hi, I am trying to run the command "forward.sel.par," however I receive the error message: "Error: could not find function 'simpleRDA2'." I have the vegan library loaded. The documentation on "varpart" has not helped me to understand why I cannot call this function. Maybe I am missing something obvious because I am still an 'R' novice. Below is a

Please help me to produce smoothed contour plots. I have dependent data generated at regular intervals of two independent variables and would like to produce smoothed contour plots - I cannot get interp (alima) to produce cubic interpolations of the data, only linear ones. I'm interested in smoothing as the data generation process is stochastic and produces small variations which I'd

when running the command > length(a <- 1:5) <- 4 there are two responses. If 'a' does not exist then the response is Error in length(a <- 1:5) <- 4 : object "a" not found If 'a' does exist then the response is Error in length(a <- 1:5) <- 4 : could not find function "<-<-" I would assume that 'length(a <- 1:5) <-

Please help me to produce smoothed contour plots. I have dependent data generated at regular intervals of two independent variables and would like to produce smoothed contour plots - I cannot get interp (alima) to produce cubic interpolations of the data, only linear ones. I'm interested in smoothing as the data generation process is stochastic and produces small variations which I'd

Hello Friends, I am new to R and stuck with a problem. i have two columns drug_A and drug_B, i have plotted a scatter plot using the ggplot2 function. My problem is with the third column, it is the p-value column. I want to color and size points differently based on the p_value, the p_value range is between 0<0.0001< 0.001<0.05<1. I used a script using the ifelse loop, but it

Would anyone help me solve my problem with R, please? I am very new to R. I am doing logistic regression analysis on the presence/absence of salamanders using several predictor variables, as shown below. I have checked my data, but I didn't find any 'NA' or empty cells. When I used step() or stepAIC to select significant predictor variables, <none>s appear to places where

Dear R Core Team, First of all, thank you for your amazing work on developing and maintaining this wonderful language. I just stumbled upon the following behavior in R version 3.6.0: format(9.91, digits = 2, nsmall = 2) format(9.99, digits = 2, nsmall = 2) yield "9.91" and " 9.99" with an extraneous whitespace. My expected output for the second command is

Dear R-collegues, I'm getting an error message (Error in round) when summarising a glm.nb model, and when using anova.negbin (in R 1.3.1 for windows): > m.nb <- glm.nb(tax ~ areal) > m.bn Call: glm.nb(formula = tax ~ areal, init.theta = 5.08829537115498, link = log) Coefficients: (Intercept) areal 3.03146 0.03182 Degrees of Freedom: 283 Total (i.e. Null); 282

The format.info() function currently takes args (x, digits = NULL, nsmall = 0), while format.default() takes many more: function (x, trim = FALSE, digits = NULL, nsmall = 0, justify = c("left", "right", "centre", "none"), width = NULL, na.encode = TRUE, scientific = NA, big.mark = "", big.interval = 3, small.mark = "",

Dear Masters, I'm driving crazy with the lowess() function.... my intent is smoothing confidence intervals for predicted y values in a linear model lm() setting since in the predict() function there exists an option for predicting NA values, I instead encounter problems when I fit a missing values x variable to the predicted terms.....,impossible task!!! I've been banging on my head

Why is there no is.Date function in R? I am running 2.1.1 does it exist in newer version? If there is a reasoning behind the lack of a is.Date function what is it? Thanks Charles -- Charles Dupont Computer System Analyst School of Medicine Phone: (615) 936-6510 Department of Biostatistics Vanderbilt University

[This turned into a bug report which will go to r-devel, so I have taken it off r-help.] Bugs reported here: (1) formatC's help page need some clarification. (2) formatC needs to treat modes "double" and "real" as equivalent. (3) format's help page or (preferably) format needs correction re the meaning of `digits' On Sun, 28 Feb 1999, Martin Maechler wrote: