On Jan 23, 2015, at 5:54 PM, JohnDee wrote:
Heinz Tuechler wrote
At 07:40 21.06.2009, J Dougherty wrote:
[...]
There are other ways of regarding the FET. Since it is precisely
what it says
- an exact test - you can argue that you should avoid carrying over any
conclusions drawn about
Section 1.1.6 of the Writing R Extensions describes the use of the inst/extdata
directory for any type or organization of data that you want to keep in the
package. None of the directories should be assumed to be writeable though... if
you want to write data then do it in the temporary
Don't worry, there are plenty of halfwits around here. However, this is about
stats theory, and not really about R, so you're better off trying
CrossValidated, aka stats.stackexchange.com
-pd
On 24 Jan 2015, at 14:26 , Ben Brooker awe@googlemail.com wrote:
Hi,
I am new to R and
Hola a todos
Hoy vi esta noticia, puede ser buena o mala, pero que una empresa enorme
mire a R es bueno, lo malo sería cerrarlo, pero como viene microsoft el
último tiempo es de esperar buenas opciónes.
Sorry I was not clearer, but I was asking an R programming question not a
theory question. I will try to clarify. If I did this analysis with a dataset
involving just one subject the summary command on the lm object would give me
a significance test on each parameter fit. The question in this
I am looking for an R package that solves Set Cover Problem. As Wikipedia
explains:
Given a set of elements [image: \{1,2,...,m\}] (called the universe) and a
set [image: S] of [image: n] sets whose union equals the universe, the set
cover problem is to identify the smallest subset of [image: S]
R-square is often a poor indicator of whether a model is appropriate or not.
While it is possible that there exists a package that implements your algorithm
(which you might find using the sos package), I would recommend that you get
some advice from an expert on how to approach this subject,
I’m trying to test what growth functions best fit individual subjects. I’m
wanting compare linear, quadratic, cubic etc. Here is the example from the
cubic curve.
b3a-by(c,id,function(x) lm(w~agec+ageq+agecub,data=x))
I can get quiet a bit of information out of sapply(b3a,summary) but it
Hi, I am analyzing the relationship between animal density and several
environmental factors using GAM in mgcv. I used Poisson distribution and
quasi-Poisson model separately because there is overdispersion. In my model,
there is a categorical predictor variable Year. However, when I compared
Hi,
I am new to R and have not had the most exposure to statistics.
I have a dataset of percentage cover (so 0-100) for certain species in 3
different shore zones (High, mid and low). The data was recorded for
different protected areas as well (17 of them) and my number of obs is
large (3358).
Hello All,
I am nearing the end of the Package BondLab. This package is for the analysis
of structured securities (MBS, REMICs, and Mortgage derivatives). I would like
to submit to CRAN but the folder structure is not standard. Indeed, I plan to
reorganize the folder structure outside the
wrong list.
Post on stats.stackexchange.com
-- Bert
Bert Gunter
Genentech Nonclinical Biostatistics
(650) 467-7374
Data is not information. Information is not knowledge. And knowledge
is certainly not wisdom.
Clifford Stoll
On Sat, Jan 24, 2015 at 1:53 AM, Mauricio Gomes
Hi Camilo,
If I understand the above, you want to find the minimum number of days
between two day-month dates when there is no information about the
year. I think if you take the difference of the two dates with the
same year and the difference of the dates after subtracting a year
from the latest
Hi Richard,
You could also do it using the package dplyr:
dta - data.frame(Name=c('John','Mary','Sam','John'),
CheckInDate=as.Date(c('1/3/2014','1/3/2014','1/4/2014','1/4/2014'),
format='%d/%m/%Y'),
Temp=c(97,98.1,97.5,99))
On Jan 24, 2015, at 8:37 AM, peter dalgaard wrote:
Don't worry, there are plenty of halfwits around here. However, this is about
stats theory, and not really about R, so you're better off trying
CrossValidated, aka stats.stackexchange.com
This is useful and correct advice, but if you want
15 matches
Mail list logo
