Displaying 20 results from an estimated 333 matches for "quadratic".

2008 Oct 22
1
Hi all, I am using quadratcount in spatstat to divide a window containing a point pattern into a grid of quadrats containing the intensity of points in each quadrat. My data is in UTM co-ordinates. My window is defined as follows: >p15<-ppp(x,y,window=owin(c(341710,342100),c(3126465,3126780)),marks=NUL L, checks=TRUE) Giving me a distance of 390m in the 'x' direction and 315m in
2005 Dec 05
2
lmer and glmmPQL
I have been looking into both of these approaches to conducting a GLMM, and want to make sure I understand model specification in each. In particular - after looking at Bates' Rnews article and searching through the help archives, I am unclear on the specification of nested factors in lmer. Do the following statements specify the same mode within each approach? m1 = glmmPQL(RICH ~ ZONE,
2016 Dec 18
2
llvm (the middle-end) is getting slower, December edition
> > >> > LVI is one of those analyses with quadratic runtime, but has a cutoff to > its search depth so that it is technically not quadratic. So increased > inlining could easily exacerbate it more than non-"quadratic" passes. > (increased inlining would also cause a general slowdown too). > > LVI is only quadratic because of...
2004 Oct 06
0
Hi, Does anybody have experience to solve an quadratic programming problem with quadratic constraints in R? It seems that the package "quadprog" only handles the quadratic programming with linear constraint. My probelm is to maximze x^T\Sigma_{xy} y, subject to x^Tx=1, y^T\Sigma_{yy} y=1, and sum(y)<t, or sum(y)=t, where x and y are t...
2005 Mar 26
1
lme: random effects of a quadratic term
Hello, I am estimating the following model: so2.lme<-lme(so2~1+I(alcadakm^2)+dia,data=subjectes2,na.action=na.omit) And when I try to plot the random effects of the quadratic term with respect to a covariate (mam) I get an error: > so2.lmeRE<-ranef(so2.lme,augFrame=T) > plot(so2.lmeRE,form=I(alcadakm^2)~mam) Error in plot.ranef.lme(so2.lmeRE, form = I(alcadakm^2) ~ mam ) : Only single effects allowed in left side of form. Any suggestion? Thanks! Montse Ru...
2016 Dec 18
0
llvm (the middle-end) is getting slower, December edition
On Sat, Dec 17, 2016 at 8:39 PM, Daniel Berlin <dberlin at dberlin.org> wrote: > >>> >> LVI is one of those analyses with quadratic runtime, but has a cutoff to >> its search depth so that it is technically not quadratic. So increased >> inlining could easily exacerbate it more than non-"quadratic" passes. >> (increased inlining would also cause a general slowdown too). >> >> > LVI is...
2017 Jul 13
3
How to formulate quadratic function with interaction terms for the PLS fitting model?
I have two ideas about it. 1- i) Entering variables in quadratic form is done with the command I (variable ^ 2) - plsr (octane ~ NIR + I (nir ^ 2), ncomp = 10, data = gasTrain, validation = "LOO" You could also use a new variable NIR_sq <- (NIR) ^ 2 ii) To insert a square variable, use syntax I (x ^ 2) - it is very important to insert I before the...
2010 Dec 04
1
Hello. I'm trying to solve a quadratic programming problem of the form min ||Hx - y||^2 s.t. x >= 0 and x <= t using solve.QP in the quadprog package but I'm having problems with Dmat not being positive definite, which is kinda okay since I expect it to be numerically semi-definite in most cases. As far as I'm aware the pr...
2009 Mar 28
1
Is there any package or operation in R designed to conduct or facilitate Quadrat Variance analysis of spatial data? Any leads would be much appreciated as I have found very little in my searches thus far. Tyler -- View this message in context: http://www.nabble.com/Quadrat-Variance-analysis-tp22752517p22752517.html Sent from the R help mailing list archive at Nabble.com.
2017 Jul 13
0
How to formulate quadratic function with interaction terms for the PLS fitting model?
Below. -- Bert Bert Gunter On Thu, Jul 13, 2017 at 3:07 AM, Luigi Biagini <luigi.biagini at gmail.com> wrote: > I have two ideas about it. > > 1- > i) Entering variables in quadratic form is done with the command I > (variable ^ 2) - > plsr (octane ~ NIR + I (nir ^ 2), ncomp = 10, data = gasTrain, validation = > "LOO" > You could also use a new variable NIR_sq <- (NIR) ^ 2 > > ii) To insert a square variable, use syntax I (x ^ 2) - it is very >...
2013 May 05
1
slope coefficient of a quadratic regression bootstrap
Hello, I want to know if two quadratic regressions are significantly different. I was advised to make the test using step 1 bootstrapping both quadratic regressions and get their slope coefficients. (Let's call the slope coefficient *â*^1 and *â*^2) step 2 use the slope difference *â*^1-*â*^2 and bootstrap the slope coeffi...
2004 Jan 13
0
Running out of memory
I'm working with large data frames and running out of memory. I hope some of you may be able to suggest a more efficient approach. I have grid/lattice data representing a time series of 1 m2 quadrats in a grassland: Each 1 cm2 cell or pixel contains one ecological state (ie grass or bare ground). The goal is to calculate, for each cell, the transition probabilities to all available
2017 Nov 28
0
Extract all point in a quadrats by spatstat package
Hi, With the following code i can divides window into quadrats and counts the numbers of points in each quadrat. library(spatstat) X <- runifpoint(50) quadratcount(X) quadratcount(X, 4, 5) quadratcount(X, xbreaks=c(0, 0.3, 1), ybreaks=c(0, 0.4, 0.8, 1)) qX <-? quadratcount(X, 4, 5) plot(X) plot(qX, add=TRUE) But I want to mark each? quadrats? and select/ extract only those points by
2017 Jul 16
2
How to formulate quadratic function with interaction terms for the PLS fitting model?
...<bgunter.4567 at gmail.com> wrote: > > Below. > > -- Bert > Bert Gunter > > > > On Thu, Jul 13, 2017 at 3:07 AM, Luigi Biagini <luigi.biagini at gmail.com> wrote: >> I have two ideas about it. >> >> 1- >> i) Entering variables in quadratic form is done with the command I >> (variable ^ 2) - >> plsr (octane ~ NIR + I (nir ^ 2), ncomp = 10, data = gasTrain, validation = >> "LOO" >> You could also use a new variable NIR_sq <- (NIR) ^ 2 >> >> ii) To insert a square variable, use syntax I...
2017 Jul 16
0
How to formulate quadratic function with interaction terms for the PLS fitting model?
...if(20) > mdl1 <-lm(y~df*I(df^2)) > mdl2 <-lm(y~df*poly(df,degree=2,raw=TRUE)) > length(coef(mdl1)) [1] 16 > length(coef(mdl2)) [1] 40 Explanation: In mdl1, I(df^2) gives the squared values of the 3 columns of df. The formula df*I(df^2) gives the 3 (linear) terms of df, the 3 pure quadratics of I(df^2), the 9 cubic terms obtained by crossing these, and the constant coefficient = 16 coefs. In mdl2, the poly() expression gives 9 variiables: 3 linear, 3 pure quadratic, 3 interactions (1.2, 1.3, 2.3) of these. The df*poly() term would then give the 3 linear terms of df, the 9 terms of...
2011 Jan 21
0
Marginality rule between powers and interaction terms in lm()
Dear all, I have a model with simple terms, quadratic effects, and interactions. I am wondering what to do when a variable is involved in a significant interaction and in a non-significant quadratic effect. Here is an example d = data.frame(a=runif(20), b=runif(20)) d\$y = d\$a + d\$b^2 So I create both an simple effect of a and a quadratic effect o...
2009 Mar 27
0