It's very simple my boy!! Do you already to play with "mar"? So..Try to
change the values this object. For example, par(..., mar=c(*5*,2,2,2)).
Bye!
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Good afternoon, gentlemen! After several days studying and researching on
categorical data (various forums with answers from the owner of the library
- all incipient) how to interpret the output the function MCMCglmm, come to
enlist the help of you, if someone has already worked with MCMCglmm funct
Good morning gentlemen!
I'm not a fan of the lattice due to a large number of procedures what should
be done to reach a simple goal, but have confess that in some cases the
graphics are way better than the graphics. Some days I have been searching
without success as is to add a cut-off point on a
Good morning gentlemen!
When I use the function nls2, and store it in an object, that object is
automatically printed, without the summary or to draw the object. For
example.
model <- nls2 (...)
Number of iterations to convergence: ...
Achieved convergence tolerance: ...
Nonlinear regression mo
Good morning gentlemen!
How using a weighted model in nls2? Values with the nls are logical since
values with nls2 are not. I believe that this discrepancy is due to I did
not include the weights argument in nls2.
Here's an example:
MOISTURE <- c(28.41640, 28.47340, 29.05821, 28.52201, 30.9
Hi Richard,
First thank you for your attention. Actually
the way it approached the examples of statements do not like a lot,
because the calculations are done separately for each factor of
interest to the interaction. Why will not it pleases me so much? Tukey's tests
as for example using the mea
It's been a few weeks I'm racking my brains on how to use the function glht
the package multcomp to test interactions. Unfortunately, the creator of the
package forgot to put a sample in pdf package how to do it. I have looked in
several places, but found nothing. If someone for the love of God ca
Good evening gentlemen!
I have a test in split-plot with randomized block design where my answer is
a binomial variable. I wonder if there is any way I can calculate the
probability of my factors considering the design errors in the case are two.
I looked at various threads here and elsewhere, a
Hi Ben!
Following his recommendations I did the following:
1st step:
I compared the best model for binomial and binomial inflates.
1.1 Best model for Binomial.
dg$resp.mumi <- cbind(dg$MUMI,dg$NT - dg$MUMI)
dg
names(dg)
mod.mumi.binomial <- glm(resp.mumi ~ factor(PARTO)*REG, family=binomial,
da
: Re: Using the zero-inflated binomial in experimental designs
Ivan Allaman yahoo.com.br> writes:
>
>
> I'm trying to use the inflated binomial distribution of zeros (since 75% of
> the values are zeros) in a randomized block experiment with four
> quantitative tre
I'm trying to use the inflated binomial distribution of zeros (since 75% of
the values are zeros) in a randomized block experiment with four
quantitative treatments (0, 0.5, 1, 1.5), but I'm finding it difficult,
since the examples available in VGAM packages like for example, leave us
unsure of ho
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