diegol gmail.com> writes:
>
>
> R version: 2.7.0
> Running on: WinXP
>
> I am trying to model damage from fire losses (given that the loss occurred).
> Since I have the individual insured amounts, rather than sampling dollar
> damage from a continuous distribution ranging from 0 to infinity, I
Thank you for your suggestions, I am sorry that
http://www.nabble.com/file/p21168216/ds2_panelA_p8_B3_dil4x.csv
ds2_panelA_p8_B3_dil4x.csv I forgot to include the concentration of Standard
to use. the first standard (A1, A2) is 67000 and dilution series is created
by diluting it 1/3. i am repost
R version: 2.7.0
Running on: WinXP
I am trying to model damage from fire losses (given that the loss occurred).
Since I have the individual insured amounts, rather than sampling dollar
damage from a continuous distribution ranging from 0 to infinity, I want to
sample from a percent damage distrib
I'm just a ggplot2 beginner, but...
It seems to me that you're mixing continuous and factor variables/concepts.
It looks to me as if ForkLength and Number are continuous values. But you'll
need to convert ForkLength into a factor before using geom="bar". I do that
and the graph "works" but the ba
Dear Leo,
> Dear R-List,
>
> I am interested in the Bayesian view on parameter estimation for multilevel
> models and ordinary regression models.
You might find Gelman & Hill's recent book to be good reading, and
there is a book in the Use-R series that focuses on using R to perform
Bayesian an
If it is only for a single coefficient you can just subtract your test-value
from the coefficient and divide by the coefficient's standard-error, which
gives you a t-value for the test (see Greene 2006).
Otherwise, lookup "linear.hypothesis" in the "car" library.
Cheers,
Daniel
--
This is very opaque to me. But if H0 is a null hypothesis (i.e. a hypothesis
about one or several coefficients in your model), then you can test linear
or nonlinear restrictions of the coefficients. Because your coefficients are
derived using your data, it appears to me you get something like a
p(H
Ben Bolker wrote:
Peter Dalgaard wrote:
Thomas Lumley wrote:
On Wed, 24 Dec 2008, Peter Dalgaard wrote:
It is a bit like the History question: "Who was what in what of whom?"
A traditional British equivalent is "Who dragged whom how many times
around the walls of where?", which does have ju
Odette Gaston gmail.com> writes:
>
> Dear all,
>
> I have a problem with accessing class attributes.
> I was unable to solve this
> yet, but someone may know how to solve it.
My best guess at your immediate problem (doing
things by hand) is that you're not using the
whole vector. From your e
Peter Dalgaard wrote:
> Thomas Lumley wrote:
>> On Wed, 24 Dec 2008, Peter Dalgaard wrote:
>
>>> It is a bit like the History question: "Who was what in what of whom?"
>>>
>>>
>>
>> A traditional British equivalent is "Who dragged whom how many times
>> around the walls of where?", which does have
Thomas Lumley wrote:
On Wed, 24 Dec 2008, Peter Dalgaard wrote:
It is a bit like the History question: "Who was what in what of whom?"
A traditional British equivalent is "Who dragged whom how many times
around the walls of where?", which does have just about enough context.
Yes. "Joshu
Bert Gunter gene.com> writes:
>
> FWIW:
>
> Good advice below! -- after all, the first rule of optimizing code is:
> Don't!
>
> For the record (yet again), the apply() family of functions (and their
> packaged derivatives, of course) are "merely" vary carefully written for()
> loops: their mai
On Wed, 24 Dec 2008, Peter Dalgaard wrote:
Ben Bolker wrote:
Khawaja, Aman wrote:
I need to answer one of the question in my open source test is: What are
the four questions asked about the parameters in hypothesis testing?
Please check the posting guide.
* We don't answer homework quest
John Fox mcmaster.ca> writes:
>
> Dear Kirk,
>
> Actually, co2 isn't a data frame but rather a "ts" (timeseries) object. A
> nice thing about R is that you can query and examine objects:
>
> > class(co2)
> [1] "ts"
[...]
Yes.
And with
> frequency(co2)
[1] 12
One gets "the number of obser
Dear R-List,
I am interested in the Bayesian view on parameter estimation for
multilevel models and ordinary regression models. AFAIU traditional
frequentist p-values they give information about p(data_or_extreme|H0).
AFAIU it further, p-values in the Fisherian sense are also no alpha/type
I erro
Hi,
You could use the "offset" argument in lm(). Here is an example:
set.seed(123)
x <- runif(50)
beta <- 1
y <- 2 + beta*x + rnorm(50)
model1 <- lm (y ~ x)
model2 <- lm (y ~ 1, offset=x)
anova(model2, model1)
Best,
Ravi.
R
Please do study the posting guide: you have not told us your platform and
it does matter.
For Windows and Mac OS X see the appropriate FAQ.
On Wed, 24 Dec 2008, Sean Zhang wrote:
Dear R-helpers:
I am new to R and would like to seek your expert opinion on installation
tip. Many thanks in adva
17 matches
Mail list logo
