Displaying 20 results from an estimated 10000 matches similar to: "smooth.spline"
2013 Feb 27
1
Finding the knots in a smoothing spline using nknots
Hi r-helpers.
Please forgive my ignorance, but I would like to plot a smoothing spline
(smooth.spline) from package "stats", and show the knots in the plot, and I
can't seem to figure out where smooth.spline has located the knots (when I
use nknots). Unfortunately, I don't know a lot about splines, but I know
that they provide me an easy way to estimate the location of local
2015 Apr 07
2
Consulta sobre el correcto uso de smoothSpline()
Hola a todos:
quiero consultarles para estar seguro de que estoy entendiendo bien el funcionamiento de la función smoothSpline() del paquete 'timeSeries'.
Tengo una serie temporal con datos mensuales a la cual quiero suavizar usando splines para, por ejemplo, comparar con otras series temporales.
Por lo que estuve viendo, me conviene usar la función smoothSpline() que se basa en
2011 Sep 20
2
Multivariate spline regression and predicted values
Hello,
I am trying to estimate a multivariate regression of Y on X with
regression splines. Y is (nx1), and X is (nxd), with d>1. I assume the
data is generated by some unknown regression function f(X), as in Y =
f(X) + u, where u is some well-behaved regression error. I want to
estimate f(X) via regression splines (tensor product splines). Then, I
want to get the predicted values for some new
2007 Jul 04
3
Problem/bug with smooth.spline and all.knots=T
Dear list,
if I do
smooth.spline(tmpSec, tmpT, all.knots=T)
with the attached data, I get this error-message:
Error in smooth.spline(tmpSec, tmpT, all.knots = T) :
smoothing parameter value too small
If I do
smooth.spline(tmpSec[-single arbitrary number], tmpT[-single arbitrary number], all.knots=T)
it works!
I just don't see it. It works for hundrets other datasets, but not for
2012 Mar 12
1
Fwd: Re[2]: B-spline/smooth.basis derivative matrices
--- On Mon, 3/12/12, aleksandr shfets <a_shfets at mail.ru> wrote:
> From: aleksandr shfets <a_shfets at mail.ru>
> Subject: Fwd: Re[2]: [R] B-spline/smooth.basis derivative matrices
> To: "Vassily Shvets" <shv736 at yahoo.com>
> Received: Monday, March 12, 2012, 5:15 PM
>
>
>
> -------- ???????????? ?????????
> --------
> ?? ????:
2009 Oct 13
2
How to choose a proper smoothing spline in GAM of mgcv package?
Hi, there,
I have 5 datasets. I would like to choose a basis spline with same knots in
GAM function in order to obtain same basis function for 5 datasets.
Moreover, the basis spline is used to for an interaction of two covarites.
I used "cr" in one covariate, but it can only smooth w.r.t 1 covariate. Can
anyone give me some suggestion about how to choose a proper smoothing spline
2010 Jun 11
1
Documentation of B-spline function
Goodmorning,
This is a documentation related question about the B-spline function in R.
In the help file it is stated that:
"df degrees of freedom; one can specify df rather than knots; bs() then chooses df-degree-1 knots at suitable quantiles of x (which will ignore missing values)."
So if one were to specify a spline with 6 degrees of freedom (and no intercept) then a basis
2012 Feb 24
1
B-spline/smooth.basis derivative matrices
Hello,
I've noticed that SPLUS seems to have a function for evaluating derivative matrices of splines. I've found the R function that evaluates matrices from 'smooth.spline'; maybe someone has written something to do the same with smooth.basis?
regards,
s
2013 Mar 11
1
Use pcls in "mgcv" package to achieve constrained cubic spline
Hello everyone,
Dr. wood told me that I can adapting his example to force cubic spline to pass through certain point.
I still have no idea how to achieve this. Suppose we want to force the cubic spline to pass (1,1), how can
I achieve this by adapting the following code?
# Penalized example: monotonic penalized regression spline .....
# Generate data from a monotonic truth.
2009 Sep 24
1
basic cubic spline smoothing
Hello,
I come from a non statistics background, but R is available to me,
and I needed to test an implementation of smoothing spline that I have
written in c++, so I would like to match the results with R (for my unit
tests)
I am following
http://www.nabble.com/file/p25569553/SPLINES.PDF SPLINES.PDF
where we have a list of points (xi, yi), the yi points are random such that:
y_i = f(x_i) +
2004 Mar 03
8
need help with smooth.spline
Dear R listers,
When using smooth.spline to interpolate data, results are generally
good. However, some cases produce totally unreasonable results.
The data are values of pressure, temperature, and salinity from a
probe that is lowered into the ocean, and the objective is to
interpolate temperature and salinity to specified pressures. While
smooth.spline provides excellent values at the
2005 Nov 23
1
1st derivative {mgcv} gam smooth
Dear R-hep,
I'm trying to get the first derivative of a smooth from a gam
model like:
model<-gam(y~s(x,bs="cr", k=5)+z) and need the derivative: ds(x)/dx. Since
coef(model) give me all the parameters, including the parameters of the
basis, I just need the 1st derivative of the basis s(x).1, s(x).2, s(x).3,
s(x).4. If the basis were generated with the function
2006 Jul 31
1
questions regarding spline functions
Greetings,
A couple general questions regarding the use of splines to interpolate depth
profile data.
Here is an example of a set of depths, with associated attributes for a given
soil profile, along with a function for calculating midpoints from a set of
soil horizon boundaries:
#calculate midpoints:
mid <- function(x) {
for( i in 1:length(x)) {
if( i > 1) {
a[i] = (x[i] -
2010 May 24
1
finding the best cubic spline fitting
Hi,
I am trying to fit cubic spline to a data on mortality rate by age and year
(1900-2008). The data is noisy and hence I would like to smooth using spline
and also extrapolate beyond 2008. Data from 1900 to 1948 are very unreliable
while data from 1948 to 2008 are reliable. I would like to have a higher
weight for data between 1948 to 2008. I am not sure how to do this. When I
smooth data from
2009 Sep 30
1
rcs fits in design package
Hi all,
I have a vector of proportions (post_op_prw) such that
>summary(amb$post_op_prw)
Min. 1st Qu. Median Mean 3rd Qu. Max. NA's
0.0000 0.0000 0.0000 0.3985 0.9134 0.9962 1.0000
> summary(cut2(amb$post_op_prw,0.0001))
[0.0000,0.0001) [0.0001,0.9962] NA's
1904 1672 1
2001 Dec 13
1
Code for Hodrick-Prescott Filter: Special Case of smooth. spline?
I've had a play with this and, due to my own short-comings, remain none the
wiser.
In particular, I'm not sure what value of 'spar' is consistent with the
magic lambda=1/1600 for quarterly data.
I initially interpreted spar as lambda and tried setting spar=1/1600. This
results in almost no smoothing while spar=1600 causes an error. The
smooth.spline function seems to want
2010 Apr 14
1
Selecting derivative order penalty for thin plate spline regression (GAM - mgcv)
Hi,
I am using GAMs (package mgcv) to smooth event rates in a penalized regression setting and I was wondering if/how one can
select the order of the derivative penalty.
For my particular problem the order of the penalty (parameter "m" inside the "s" terms of the formula argument) appears to
have a larger effect on the AIC/deviance of the estimated model than the
2003 May 08
2
natural splines
Apologies if this is this too obscure for R-help.
In package splines, ns(x,,knots,intercept=TRUE) produces an n by K+2
matrix N, the values of K+2 basis functions for the natural splines with K
(internal) knots, evaluated at x. It does this by first generating an
n by K+4 matrix B of unconstrained splines, then postmultiplying B by
H, a K+4 by K+2 representation of the nullspace of C (2 by K+4),
2008 May 01
1
Optimal knot locations for splines
Suppose I have two variables, x and y. For a fixed number of knots, I want
to create a spline transformation of x such that a loss function is
minimized. Presumably, this loss function would be least squares, i.e. sum
(f(x)-y)^2. The spline transformations would be linear, quadratic or
cubic. I know I can solve this problem using some optimization function in
R, but I was wondering if anyone
2007 Jun 25
1
gam function in the mgcv library
I would like to fit a logistic regression using a smothing spline, where the spline is a piecewise cubic polynomial. Is the knots option used to define the subintervals for each piece of the cubic spline? If yes and there are k knots, then why does the coefficients field in the returned object from gam only list k coefficients? Shouldn't there be 4k -4 coefficients?
Sincerely,
Bill