search for: antilogged

Dear R-users, I have a basic question about how to determine the antilog of a variable. Say I have some number, x, which is a factor of 2 such that x = 2^y. I want to figure out what y is, i.e. I am looking for the antilog base 2 of x. I have found log2 in the Reference Manual. But I am struggling how to get the antilog of that. Any help will be appreciated! > version platform

Hi, I am using R for microarray data anlaysis. When I normalize my data, it converts all my data in to log base 2 values. how can I convert back to log base 10..is there any function in R which I can use or how can I take anti log. or is there any function in R for antilog. Please let me know,..if anyone knows.. Thank you so much, Saurin ===== Saurin's WebWorld:

Hi, I am trying to find out how to interpret the summary output from a neg bin GLM? I have 3 significant variables and I can see whether they have a positive or negative effect, but I can't work out how to calculate the magnitude of the effect on the mean of the dependent variable. I used a log link function so I think I might have to use the antilogs of the coefficients but I have no idea

Hi, This might be me missing something painfully obvious but why does the cube root of the following produce an NaN? > (-4)^(1/3) [1] NaN > As we can see: > (-1.587401)^3 [1] -4 Thanks! Greg

There are a couple of points to keep in mind when doing a log-transform of an exponential model, such as -- y = a*exp(b*x) 1. The implicit statistical model is multiplicative in the error. The implied statistical model of the log transform is -- log(y) = log(a) + b*x + u which implies -- y = a*exp(b*x)*exp(u) A linear regression in the log

Hi all I have another GLIM question. I have been using R as well as Genstat (version 6) in order to fit GLIM models to the data (displayed below). The same models are fitted but the answers supplied by the two packages are not the same. Why? Can anyone help? A discription of the data and the type of model/s fitted can be found below. Regards Allan The

Hi all, I have a dataset which consists of 2 columns. I'd like to plot them on a x-y scatter plot and fit an exponential trendline. I'd like R to determine the equation for the trendline and display it on the graph. Since I am new to R (and statistics), any advice on how to achieve this will be greatly appreciated. Many thanks, Chris -- View this message in context:

...t with x sorted along y. o plot.formula now allows ylab to be set o plotmath had trouble with paste()'ing expressions o plotting math expressions now also works for objects of mode "call" (in particular on the result of substitute()) o locator() on log axes: value antilogged twice o (a real oldie - and trival too) is.recursive now TRUE for expressions o sanitised delete.response o x[["a",]] could crash R o strwidth() crashed R if no device open o predict inconsistencies with offsets straightened out o tapply goofed when FUN ret...

...t with x sorted along y. o plot.formula now allows ylab to be set o plotmath had trouble with paste()'ing expressions o plotting math expressions now also works for objects of mode "call" (in particular on the result of substitute()) o locator() on log axes: value antilogged twice o (a real oldie - and trival too) is.recursive now TRUE for expressions o sanitised delete.response o x[["a",]] could crash R o strwidth() crashed R if no device open o predict inconsistencies with offsets straightened out o tapply goofed when FUN ret...

Hi all, Im a little bit confused concerning the effect() command, effects package. I have done several glm models with family=quasipoisson: model <-glm(Y~X+Q+Z,family=quasipoisson) and then used results.effects <-effect("X",model,se=TRUE) to get the "adjusted means". I am aware about the debate concerning adjusted means, but you guys just have to trust me - it