> On Dec 29, 2015, at 10:35 PM, Anindya Sankar Dey wrote:
>
> Hi All,
>
> The fmsb package has a function called Variance Inflation Factor and it
> states the definition of the function as follows:-
>
> "To evaluate multicolinearity of multiple regression model, calculating the
> variance infl
Hi
You probably can do also only
Irig.tot <- (Irrig>HM)*6.123
to get desired vector without any further typing around.
Logical vector can be treated as c(0,1) vector. FALSE equals zero and TRUE
equals 1 on calculations.
Maybe you shall spend some time reading R intro manual which can serve yo
Hi All,
The fmsb package has a function called Variance Inflation Factor and it
states the definition of the function as follows:-
"To evaluate multicolinearity of multiple regression model, calculating the
variance inflation factor (VIF) from the result of lm(). If VIF is more
than 10, multicoli
Hi Liliana,
see inline comments
On Sat, Jul 18, 2015 at 5:57 AM, Liliana Zazueta
wrote:
> Excuse me I have this dude,
Suppressing my desire to make a bad joke, I think you mean "doubt"
> how to make that Rgraphviz graphic without
> intersection between nodes and edges?
>
> I can't test this
> On Dec 29, 2015, at 5:33 AM, Frank van Berkum
> wrote:
>
> Hi all,
> My problem is the following.
> Suppose I have a dataset with observations Y and explanatory variables X1,
> ..., Xn, and suppose one of these explanatory variables is geographical area
> (of which there are ten, j=1,...,1
On 29/12/15 16:59, Ryan Derickson wrote:
I do not feed trolls.
cheers,
Rolf Turner
--
Technical Editor ANZJS
Department of Statistics
University of Auckland
Phone: +64-9-373-7599 ext. 88276
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On 29/12/15 15:21, Oliver Keyes wrote:
I do not feed trolls.
cheers,
Rolf Turner
--
Technical Editor ANZJS
Department of Statistics
University of Auckland
Phone: +64-9-373-7599 ext. 88276
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On 30/12/15 02:33, Frank van Berkum wrote:
Hi all, My problem is the following. Suppose I have a dataset with
observations Y and explanatory variables X1, ..., Xn, and suppose one
of these explanatory variables is geographical area (of which there
are ten, j=1,...,10). For some observations I
Hi Petr
I do thé calculation left as follows
Irrig=qWC1
Irrig [Irrig>HM]=-1
Irrig[Irrig>0]=0
Irrig.tot=-Irrig*6.123 #6.123 is the hydraulic conductivity at saturation
And I got the vector needed
Cheers
Makram
Le 28 déc. 2015 12:15, "PIKAL Petr" a écrit :
> Hi
>
> On top of answers you have got h
Hi Petr
I am adjusting my email and sorry for thé inconvenience
I read about these commands. The method is good for my case with threshold
of .02.
I need just to have a vector with the values of the réd points in réd
equal to 1-do you have an idea how to do it?-
so I could calculate total irrigati
Thanks a lot John. Forgot I could arbitrarily change the class of objects,
which against all critics, can be very helpful at times.
Best,
Axel.
> On Dec 29, 2015, at 9:35 AM, Fox, John wrote:
>
> Dear Axel,
>
> If you look at the content of the list returned by glm.fit, you'll see that
>
Excuse me I have this dude, how to make that Rgraphviz graphic without
intersection between nodes and edges?
If answer me I will be eternally gratefull!
[[alternative HTML version deleted]]
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Dear i optimized the gama and beta value using simmulation. if i run this code
it generate very small value of beta. Could any one help me in this regard. i
use gbs package to generate data.
gama=1.0
beta=1.3
n=25
iterCount=1000
for(i in 1:iterCount){
x<-rgbs(n,gama,beta)
P<-function(theta,
Hi all,
My problem is the following.
Suppose I have a dataset with observations Y and explanatory variables X1, ...,
Xn, and suppose one of these explanatory variables is geographical area (of
which there are ten, j=1,...,10). For some observations I know the area, but
for others it is unknown
Dear Axel,
If you look at the content of the list returned by glm.fit, you'll see that it
contains almost everything in a "glm" object, and what's needed to compute the
coefficient covariance matrix. Here's one way to do what you want (but note
that your example was faulty in that you didn't in
Hello,
Is it possible to extract or compute the standard errors of model coefficients
from a glm.fit object? This can be easily done from a fitted glm object, but I
need glm.fit.
set.seed(1)
n <- 100
x <- rnorm(n)
y1 <- rnorm(n)
y2 <- rbinom(n, 1, .25)
M1 <- glm (y1 ~ x)
M2 <- glm.fit(x = x,
Hi
First you shall adjust your mail client to send post in plain text not HTML, as
suggested by Posting guide. It shall be available in gmail too.
Second you do not run my code:-(
You run **your** code which is (slightly) **similar** to the code I sent you
however it is completely wrong. If you
Hi Petr
I runned the code you gave me as following, and I am adjusting for the
threshold as suggested,
sss<-smooth.spline(qWC1, tint, nknots=length(tint)/2)
peak <- which.max(predict(sss)$y) #qWC1=temp$theta mtime=temp$int
baseline <- min(predict(sss)$y)
vyska <- predict(sss)$y[peak]
# 50%
Hi Petr,
I apologize It was my first time using r-help so I didn't know how to
replay to email to all or not,
I am replaying to all for this email,
Many thanks for the code, I am trying to use it,
please find attached the data file in csv,
following are the first lines of code to read the data an
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