Displaying 20 results from an estimated 200 matches similar to: "which coefficients for a gam(mgcv) model equation?"
2011 Dec 10
2
efficiently finding the integrals of a sequence of functions
Hi folks,
I am having a question about efficiently finding the integrals of a list of
functions. To be specific,
here is a simple example showing my question.
Suppose we have a function f defined by
f<-function(x,y,z) c(x,y^2,z^3)
Thus, f is actually corresponding to three uni-dimensional functions
f_1(x)=x, f_2(y)=y^2 and f_3(z)=z^3.
What I am looking for are the integrals of these three
2004 Jul 10
1
Exact Maximum Likelihood Package
Dear R users,
I am a mathematics postdoc at UC Berkeley. I have written a package
in a Computational Algebra System named Singular
http://www.singular.uni-kl.de
to compute the Maximum Likelihood of a given probability distribution over
several discrete random variables. This package gives exact answers to the
problem. But more importantly, it gives All MLE solutions.
My understanding is that
2012 Mar 20
1
MA process in panels
Dear R users,
I have an unbalanced panel with an average of I=100 individuals and a total
of T=1370 time intervals, i.e. T>>I. So far, I have been using the plm
package.
I wish to estimate a FE model like:
res<-plm(x~c+v, data=pdata_frame, effect="twoways", model="within",
na.action=na.omit)
?where c varies over i and t, and v represents an exogenous impact on x
2009 Aug 24
2
Formulas in gam function of mgcv package
Dear R-experts,
I have a question on the formulas used in the gam function of the mgcv
package.
I am trying to understand the relationships between:
y~s(x1)+s(x2)+s(x3)+s(x4)
and
y~s(x1,x2,x3,x4)
Does the latter contain the former? what about the smoothers of all
interaction terms?
I have (tried to) read the manual pages of gam, formula.gam, smooth.terms,
linear.functional.terms but
2009 Aug 24
2
Formulas in gam function of mgcv package
Dear R-experts,
I have a question on the formulas used in the gam function of the mgcv
package.
I am trying to understand the relationships between:
y~s(x1)+s(x2)+s(x3)+s(x4)
and
y~s(x1,x2,x3,x4)
Does the latter contain the former? what about the smoothers of all
interaction terms?
I have (tried to) read the manual pages of gam, formula.gam, smooth.terms,
linear.functional.terms but
2003 Nov 10
1
ts package function filter: mismatch between function action and help (PR#5017)
Dear people,
I'm running
RedHat 9.0
and
R : Version 1.7.1 (2003-06-16)
from the help file
# Usage:
#
# filter(x, filter, method = c("convolution", "recursive"),
# sides = 2, circular = FALSE, init)
# init: for recursive filters only. Specifies the initial values of
# the time series just prior to the start value, in reverse
# time
2013 Aug 23
1
Setting up 3D tensor product interactions in mgcv
Hi,
I am trying to fit a smoothing model where there are three dimensions
over which I can smooth (x,y,z). I expect interactions between some,
or all, of these terms, and so I have set up my model as
mdl <- gam(PA ~ s(x) + s(y) + s(z) + te(x,y) + te(x,z) + te(y,z) +
te(x,y,z),...)
I have recently read about the ti(), "tensor product interaction
smoother", which takes care of these
2010 Sep 08
11
problem with outer
Hello,
i wrote this function guete and now i want to plot it: but i get this error
message. i hope someone can help me.
Error in dim(robj) <- c(dX, dY) :
dims [product 16] do not match the length of object [1]
p_11=seq(0,0.3,0.1)
p_12=seq(0.1,0.4,0.1)
guete = function(p_11,p_12) {
set.seed(1000)
S_vek=matrix(0,nrow=N,ncol=1)
for(i in 1:N) {
X_0=rmultinom(q-1,size=1,prob=p_0)
2012 Mar 23
3
R numerical integration
Hi all,
Is there any other packages to do numerical integration other than the
default 'integrate'?
Basically, I am integrating:
integrate(function(x) dnorm(x,mu,sigma)/(1+exp(-x)),-Inf,Inf)$value
The integration is ok provided sigma is >0.
However, when mu=-1.645074 and sigma=17535.26
It stopped working. On the other hand, Maple gives me a value of
0.5005299403.
It is an
2001 Oct 22
2
OT: compare several graphs
Hi all,
this is OT, but maybe someone can give me a clue. I've got data from eye
tracker experiments (750 data points). These figures show how the data
lock like
|** * ***** |*** ******
| ** **** | * *
| | * *
| | *
|-------------- |---------------
Y axes display velocity, x axes display time, * are the data points.
2003 Apr 21
2
piece wise functions
Hello,
Apologies if this question has already arised, hope you can
help me to the find the solution to this or point the place to look at.
I have a multidimensional piece-wise regression linear problem, i.e.
to find not only the regression coefficients for each "interval" but
also the beginning and ends of the intervals.
To simplify it to the one dimensional case and
two intervals,
2013 Nov 19
1
Generación de números aleatorios. Mixtura k-puntos
Saludo cordial para cada uno.
Les pido ayuda para generar números aleatorios de una mixtura k-puntos.
Sabemos que la función de distribución F es una mixtura k-puntos si es de
la forma F(x) = p_1 F_1(x) + p_2 F_2(x) + … + p_k F_k(x), donde F_j es una
función de distribución de probabilidad, p_j > 0 y suma(p_j) = 1, para j =
1, 2, …, k.
En mi caso particular F es la suavización de la
2000 Oct 03
5
Where is gam?
I noticed that there is no generalised additive model functions in R
(1.1.1) ... is there a package that implements them?
Thanks
Prasad
*****************************************************************
Mr. Anantha Prasad, Ecologist/GIS Specialist
USDA Forest Service, 359 Main Rd.
Delaware OHIO 43015 USA
Ph: 740-368-0103 Email: aprasad at fs.fed.us
Web:
2006 Nov 18
1
Questions regarding "integrate" function
Hi there. Thanks for your time in advance.
I am using R 2.2.0 and OS: Windows XP.
My final goal is to calculate 1/2*integral of
(f1(x)^1/2-f2(x)^(1/2))^2dx (Latex codes:
$\frac{1}{2}\int^{{\infty}}_{\infty}
(\sqrt{f_1(x)}-\sqrt{f_2(x)})^2dx $.) where f1(x) and f2(x) are two
marginal densities.
My problem:
I have the following R codes using "adapt" package. Although "adapt"
2013 Oct 19
2
ivreg with fixed effect in R?
I want to estimate the following fixed effect model:
y_i,t = alpha_i + beta_1 x1_t + beta_2 x2_i,tx2_i,t = gamma_i + gamma_1
x1_t + gamma_2 Z1_i + gamma_3 Z2_i
I can use ivreg from AER to do the iv regression.
fm <- ivreg(y_i,t ~ x1_t + x2_i,t | x1_t + Z1_i + Z2_i,
data = DataSet)
But, I'm not sure how can I add the fixed effects.
Thanks!
[[alternative HTML
2016 Sep 13
3
undef * 0
Hi Soham,
You're right that in LLVM IR arithmetic (with the current definition
of `undef`) is not distributive. You can't replace `A * (B + C)` with
`A * B + A * C` in general, since (exactly as you said) for A =
`undef`, B = `1`, C = `-1` the former always computes `0` while the
latter computes `undef`. This is fundamentally because replacing `A *
(B + C)` with `A * B + A * C`
2006 Jan 20
1
Calling MySQL 5 stored procedures from app_mysql
Hello all.
I am trying to use app_mysql.
It works for selects and functions, but does not want to work with
procedures.
Pls have a look:
Calling function:
CREATE FUNCTION f_1(a VARCHAR(20)) RETURNS INTEGER RETURN (SELECT count(*)
from peer where name = a);
Result:
-- Executing Macro("IAX2/100-3", "local|100") in new stack
-- Executing MYSQL("IAX2/100-3",
2016 May 30
3
Loads and stores of unsized types?
This came up in D20764, this IR verifies today:
%X = type opaque
define void @f_0(%X* %ptr) {
%t = load %X, %X* %ptr
ret void
}
define void @f_1(%X %val, %X* %ptr) {
store %X %val, %X* %ptr
ret void
}
which I found surprising -- what does it mean to load / store values
of unknown sizes? Passing it to llc fails an assertion. Are there
legitimate cases where we'd want to generate
2009 May 06
0
bivariate normal and rho
Hi,
Let f(rho) = E[F_1(x) F_2(y)], i.e f(rho) is the expectation of
F(x) * F(y) with respect to the bivariate Gaussian density with mean 0
and covariance matrix [1 rho; rho 1].
Moreover, assume F_1(x) and F_2(y) to be increasing functions of x and y
respectively.
I was wondering if it was true that f(rho) is an increasing function of rho.
If so, are there any references?
Best,
Agos
2005 Apr 22
1
lme4: apparently different results between 0.8-2 and 0.95-6
I've been using lme4 to fit Poisson GLMMs with crossed random effects. The
data are counts(y) sampled at 55 sites over 4 (n=12) or 5 (n=43) years. Most
models use three fixed effects: x1 is a two level factor; x2 and x3 are
continuous. We are including random intercepts for YEAR and SITE. On
subject-matter considerations, we are also including a random coefficient
for x3 within YEAR.