Hi,
I'm using the package gnm to perform non-linear models and I cannot
find how to write the formula for a power function model.
The equation is something like (1) y ~ A * x^B or (2)y ~ A *
B^x.
I guess it is using the nonlin function Mult(), but couldn't find how.
Thank you for y
hey, how can i plot this function?
n=1000
m=2
k=n/m
N=100
myfun <- function(n, m, alpha = .05, seeder = 1000) {
l=matrix(0,nrow=m,ncol=N)
for(i in 1:N){
set.seed(i)
for(j in 1:m){
x=rnorm(n,0,0.5)
y=rnorm(n,0,0.8)
l[j,i]=cor((x[(((j-1)*k)+1):(((j-1)*k)+k)]),
(y[(((j-1)*k)+1):(((j-1)*k)+k)]))
}
}
hi, the part with the power function does not work. this is the " gute "
function in my programm. because i´m not shure on what dependet my power
function gute. and ofcourse the graphik does not work. thnx a lot:)
regards
Kaja
Date: Fri, 24 Sep 2010 19:21:17 -0700
From: ml-node+2653667-1721
Hi,
What part of your code does not work or does not do what you want? I
am guessing that you want gute to return more than a single value
(which is what it does in your code). Can you show us an example of
the results you would like?
Best regards,
Josh
I reworked some of your code to simpl
Hi, at first, i´m from germany, so sorry for my bad english. but i need ur
help in R to programm a power function and to make at last a graphik of it.
i have already tried my best. but it doesn´t work.the topic is: the
homogeneity test of correlation based entropy.
so it means, that i have to
On 12-May-09 12:00:50, Steve Candy wrote:
> Hi All
> This is a general stats problem that I am dealing with using R,
> so any help is greater appreciated.
>
> I have two lognormal distributions with means M1 and M2.
> If we have:
>
> H0: log(M1/M2)=0
>
> H1: log(M1/M2) !=0 equivalent to log(M1/M
Hi All
This is a general stats problem that I am dealing with using R, so any help is
greater appreciated.
I have two lognormal distributions with means M1 and M2.
If we have:
H0: log(M1/M2)=0
H1: log(M1/M2) !=0 equivalent to log(M1/M2)=log(1+P) where P<0 or P>0.
If we calculate the power fo
On Mon, 2007-11-05 at 17:50 +0100, Duccio - wrote:
> I would like to fit a power model of type:
> y=b*x(^z)
> to my data (having y as the response and x as the predictor variables).
> I could not use linear models like y~x since R should estimate the parameter
> z and not only the coefficient b.
>
I would like to fit a power model of type:
y=b*x(^z)
to my data (having y as the response and x as the predictor variables).
I could not use linear models like y~x since R should estimate the parameter
z and not only the coefficient b.
Thus I need a package and a function! Any suggestions?
Thanks
D
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