Displaying 20 results from an estimated 110 matches similar to: "linear model with equality and inequality (redundant) constraints"
2007 Mar 15
0
Covariance matrix calc method question
I have been comparing the output of an R package to S+Finmetrics and I
notice that
the covariance matrix outputted by the two procedures is different. The
R package
computes the covariance matrix using Method 1 and I think ( but I'm not
sure ) that S+Finmetrics computes it
using Method 2.
I put in a correctionfactor (see below ) in to Method 2 in order to deal
with the fact that the var
2020 Nov 03
2
Query on constrained regressions using -mgcv- and -pcls-
Hello all,
I'll level with you: I'm puzzled!
How is it that this constrained regression routine using -pcls- runs
satisfactorily (courtesy of Tian Zheng):
library(mgcv)
options(digits=3)
x.1=rnorm(100, 0, 1)
x.2=rnorm(100, 0, 1)
x.3=rnorm(100, 0, 1)
x.4=rnorm(100, 0, 1)
y=1+0.5*x.1-0.2*x.2+0.3*x.3+0.1*x.4+rnorm(100, 0, 0.01)
x.mat=cbind(rep(1, length(y)), x.1, x.2, x.3, x.4)
2013 Jul 19
0
mgcv: Impose monotonicity constraint on single or more smooth terms
Dear R help list,
This is a long post so apologies in advance. I am estimating a model with the mgcv package, which has several covariates both linear and smooth terms. For 1 or 2 of these smooth terms, I "know" that the truth is monotonic and downward sloping. I am aware that a new package "scam" exists for this kind of thing, but I am in the unfortunate situation that I am
2010 Dec 06
1
use pcls to solve least square fitting with constraints
Hi,
I have a least square fitting problem with linear inequality
constraints. pcls seems capable of solving it so I tried it,
unfortunately, it is stuck with the following error:
> M <- list()
> M$y = Dmat[,1]
> M$X = Cmat
> M$Ain = as.matrix(Amat)
> M$bin = rep(0, dim(Amat)[1])
> M$p=qr.solve(as.matrix(Cmat), Dmat[,1])
> M$w = rep(1, length(M$y))
> M$C = matrix(0,0,0)
2004 Mar 01
1
non-negative least-squares
Hi all,
I am trying to do an inversion of electromagnetic data with non-negative
least squares method (Tikhonov regularisation) and have got it
programmed in S-Plus. However I am trying to move all my scripts from
S-Plus to R.
Is there an equivalent to nnls.fit in R?
I think this can be done with pcls? Right?
S-Plus script: A, L and data are matrices, lambda is a vector of
possible lambda
2009 Feb 25
1
monotonic GAM with more than one term
Hi,
Does anyone know how to fit a GAM where one or more smooth terms are
constrained to be monotonic, in the presence of "by" variables or
other terms? I looked at the example in ?pcls but so far have not been
able to adapt it to the case where there is more than one predictor.
For example,
require(mgcv)
set.seed(0)
n<-100
# Generate data from a monotonic truth.
2003 Sep 26
1
least squares regression using (inequality) restrictions
Dear R Users,
I would like to make a lesast squares regression similar to that what is
done by the command "lm". But additionally, I would like to impose some
restrictions:
1) The sum of all regression coefficients should be equal to 1.
2) Each coefficient should assume a value between 0 and 1. (inequality
restrictions)
Which command is the best to use in order to solve this problem
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.
2007 Nov 25
1
GAM with constraints
Hi,
I am trying to build GAM with linear constraints, for a general link
function, not only identity. If I understand it correctly, the function
pcls() can solve the problem, if the smoothness penalties are given.
What I need is to incorporate the constraints before calculating the
penalties. Can this be done in R?
Any help would be greately appreciated.
--
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2012 Oct 19
2
Which package/function for solving weighted linear least squares with inequality and equality constraints?
Dear All,
Which package/function could i use to solve following linear least square
problem?
A over determined system of linear equations is given. The nnls-function may
would be a possibility BUT:
The solving is constrained with
a inequality that all unknowns are >= 0
and a equality that the sum of all unknowns is 1
The influence of the equations according to the solving process is
2010 Jan 21
1
Double inequality with plotmath
Hello,
I'm fairly new to R and I can't work out how to produce a double
inequality like (LaTeX) $0 \leq x \leq 1$ in the legend of a graph. If
I try
> legend(50, 0.1, legend = c(expression(0 <= x <= 1), c(2 <= x <= 3)), pch = c(1,1), col = c(2, 3))
then I get an error message "unexpected '<=' in ...". I've checked the
help files for plotmath and
2009 Jul 17
0
Inequality constraints in GMM estimation?
I have a relatively simple finance application of GMM. Given the moment
condition:
E[m*R]=0
where m=m[theta]
I would like to constrain m>0. Any ideas?
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2006 Sep 22
2
inequality with NA
Dear everybody!
take a<-c(5,3,NA,6).
if(a[1]!=NA){b<-7}
if(a[3]!=5){b<-7}
if(a[3]!=NA){b<-7}
if(a[3]==NA){b<-7}
will alltogeather return
Fehler in if (a[1] != NA) { : Fehlender Wert, wo TRUE/FALSE n?tig ist
(or simularly). Somehow this is logical. But how else should I get out,
whether a certain vector-component has an existing value?
Thank you in advance!
Yours,
Mag. Ferri
2012 Jul 12
0
Enforcing inequality bounds and heteroscedasticity in a GAM or GLM
I have a spatial salinity field s and a model g(s) ~ Xb where the X comes from slightly modified GAM basis functions.
I am trying to deal with the following set of requirements:
1. The underlying physics are linear, and plain salinity (the identity link) is the correct response to my covariates.
2. Dispersion (variance or sd) is almost certainly proportional to the mean.
3. The data s(x,y)
2008 Dec 28
1
Logistic regression with rcs() and inequality constraints?
Dear guRus,
I am doing a logistic regression using restricted cubic splines via
rcs(). However, the fitted probabilities should be nondecreasing with
increasing predictor. Example:
predictor <- seq(1,20)
y <- c(rep(0,9),rep(1,10),0)
model <- glm(y~rcs(predictor,n.knots=3),family="binomial")
print(1/(1+exp(-predict(model))))
The last expression should be a nondecreasing
2011 Sep 08
3
global optimisation with inequality constraints
Dear All,
I would like to minimise a nonlinear function subject to linear inequality constraints as part of an R program. I have been using the constrOptim function. I have tried all of the methods that come with Optim, but nothing finds the correct solution. If I use the correct solution as the vector of starting values, though, my program does output the correct solution and optimum - the
2011 Jul 10
1
Chebyshev Inequality — MVUE
Hello,
I was interested in trying to write an R script to calculate a UCL for a lognormal distribution using the Chebyshev Inequality — MVUE Approach (based on EPA’s guidance found in http://www.epa.gov/oswer/riskassessment/pdf/ucl.pdf). This looks like it should be straight forward, but I am need to calculate an MVUE for the population mean and an MVUE for the population variance, which requires
2009 Mar 15
2
Testing for Inequality à la "select case"
Using R 2.7.0 under WinXP.
I need to write a function that takes a non-negative vector and returns the
parallell maximum between a percentage of this argument and a fixed value.
Both the percentages and the fixed values depend on which interval x falls
in. Intervals are as follows:
>From | To | % of x | Minimum
2006 Sep 04
2
Fitting generalized additive models with constraints?
Hello,
I am trying to fit a GAM for a simple model, a simple model, y ~ s(x0) +
s(x1) ; with a constraint that the fitted smooth functions s(x0) and s(x1)
have to each always be >0.
>From the library documentation and a search of the R-site and R-help
archives I have not been able to decipher whether the following is possible
using this, or other GAM libraries, or whether I will have to try
2013 Mar 06
1
Constrained cubic smoothing spline
Hello everone,
Anyone who knows how to force a cubic smoothing spline to pass through a particular point?
I found on website someone said that we can use "cobs package" to force the spline pass through certain points or impose shape constraints (increasing, decreasing). However, this package is using B-spline and can only do linear and quadratic