search for: antilogs

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:

...ummary 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 how this relates to the dependent variable?? Any help would be much appreciated. My model and output is shown below. Thanks Anna Call: glm.nb(formula = Pass ~ Dist + Time + Wind, data = bats, link = "log", init.theta = 0.8510838809) Devi...

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:

I've put up R-0.63.3.tgz up for FTP from Auckland some minutes ago. As usual, don't get it from there unless you are desperate, but wait for it to be mirrored at a CRAN site near you within a day or two. For those who *are* desperate, I've left a copy in ftp://blueberry.kubism.ku.dk/pub/R-devel/R-0.63.3.tgz (Be gentle, that's my desktop PC!) There's also a version split in

I've put up R-0.63.3.tgz up for FTP from Auckland some minutes ago. As usual, don't get it from there unless you are desperate, but wait for it to be mirrored at a CRAN site near you within a day or two. For those who *are* desperate, I've left a copy in ftp://blueberry.kubism.ku.dk/pub/R-devel/R-0.63.3.tgz (Be gentle, that's my desktop PC!) There's also a version split in

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