Displaying 20 results from an estimated 7000 matches similar to: "A contour plot question - vis.gam () function in "mgcv""
2009 Oct 13
1
vis.gam() contour plots
Greetings,
I have what I hope is a simple question. I would like to change my
contour interval on the vis.gam( plot.type="contour") in the mgcv
package. Is this a situation where I need to modify the function or is
there a default value I can change?
Thanks
2008 Mar 18
1
How to reverse colors in filled.contour?
Hi,
I am plotting values of log(hazards ratio) as a function of two predictors,
using the plotting function filled.contour(). Here is a simple simulated
example of this:
x <- seq(0,1, length=20)
y <- seq(0,1, length=20)
z <- outer(x,y, function(x,y) x^2 + y^2 )
zmat <- matrix( rexp(n=400, rate = z+0.001), 20, 20)
filled.contour(x, y, log(zmat),
2012 Jul 30
2
mgcv 1.7-19, vis.gam(): "invalid 'z' limits'
Hi everyone,
I ran a binomial GAM consisting of a tensor product of two continuous
variables, a continuous parametric term and crossed random intercepts on a
data set with 13,042 rows. When trying to plot the tensor product with
vis.gam(), I get the following error message:
Error in persp.default(m1, m2, z, col = col, zlim = c(min.z, max.z), xlab =
view[1], :
invalid 'z' limits
In
2011 Aug 31
1
Gradients in optimx
Hi Reuben,
I am puzzled to note that the gradient check in "optimx" does not work for you. Can you send me a reproducible example so that I can figure this out?
John - I think the best solution for now is to issue a "warning" rather than an error message, when the numerical gradient is not sufficiently close to the user-specified gradient.
Best,
Ravi.
2011 Sep 28
1
Download statistics for a package
Hi,
How can I get information on how many times a particular package has been downloaded from CRAN?
Thanks,
Ravi.
-------------------------------------------------------
Ravi Varadhan, Ph.D.
Assistant Professor,
Division of Geriatric Medicine and Gerontology School of Medicine Johns Hopkins University
Ph. (410) 502-2619
email: rvaradhan@jhmi.edu<mailto:rvaradhan@jhmi.edu>
[[alternative
2013 Jan 30
1
starting values in glm(..., family = binomial(link =log))
Try this:
Age_log_model = glm(Arthrose ~ Alter, data=x, start=c(-1, 0), family=quasibinomial(link = log))
Ravi
Ravi Varadhan, Ph.D.
Assistant Professor
The Center on Aging and Health
Division of Geriatric Medicine & Gerontology
Johns Hopkins University
rvaradhan@jhmi.edu<mailto:rvaradhan@jhmi.edu>
410-502-2619
[[alternative HTML version deleted]]
2012 Apr 19
4
Column(row)wise minimum and maximum
Hi,
Currently, the "base" has colSums, colMeans. It seems that it would be useful to extend this to also include colMin, colMax (of course, rowMin and rowMax, as well) in order to facilitate faster computations for large vectors (compared to using apply). Has this been considered before? Please forgive me if this has already been discussed before.
Thanks,
Ravi
Ravi Varadhan, Ph.D.
2004 Dec 03
3
Computing the minimal polynomial or, at least, its degree
Hi,
I would like to know whether there exist algorithms to compute the
coefficients or, at least, the degree of the minimal polynomial of a square
matrix A (over the field of complex numbers)? I don't know whether this
would require symbolic computation. If not, has any of the algorithms been
implemented in R?
Thanks very much,
Ravi.
P.S. Just for the sake of completeness, a
2005 Apr 20
3
Keeping factors with zero occurrences in "table" output
Dear R group,
I have a data frame which contains data on preferences on 7 items (ranks 1
through 7) listed by each participant. I would like to tabulate this in a
7x7 table where the rows would be the items and the columns would be the
number of times that item received a particular rank.
I tried doing this by creating a matrix by "rbind"ing each vector obtained
using
2011 Aug 26
2
How to generate a random variate that is correlated with a given right-censored random variate?
Hi,
I have a right-censored (positive) random variable (e.g. failure times subject to right censoring) that is observed for N subjects: Y_i, I = 1, 2, ..., N. Note that Y_i = min(T_i, C_i), where T_i is the true failure time and C_i is the censored time. Let us assume that C_i is independent of T_i. Now, I would like to generate another random variable U_i, I = 1, 2, ..., N, which is
2011 Jun 24
4
How to capture console output in a numeric format
Hi,
I would like to know how to capture the console output from running an algorithm for further analysis. I can capture this using capture.output() but that yields a character vector. I would like to extract the actual numeric values. Here is an example of what I am trying to do.
fr <- function(x) { ## Rosenbrock Banana function
on.exit(print(f))
x1 <- x[1]
x2 <- x[2]
2011 Oct 27
2
vis.gam zlab problem
I am using the mgcv package to develop vis.gam plots and having trouble
figuring out how to relabel the z-axis (image attached). It is currently
labeled as "linear predictor," but I would like to change it to a different
name. Currently I am using this code:
vis.gam(model1,theta=320,ticktype="detailed",color="gray",nCol=12,
zlab="BCS")
However, when run
2005 Nov 21
4
Can't figure out warning message
Hi,
I apologize for the previous posting, where the message was not formatted
properly. Here is a better version:
I have written the following function to check whether a vector has elements
satisfying monotonicity.
is.monotone <- function(vec, increase=T){
ans <- TRUE
vec.nomis <- vec[!is.na(vec)]
if (increase & any(diff(vec.nomis,1) < 0, na.rm=T)) ans <- FALSE
2012 Mar 29
0
multiple plots in vis.gam()
Hi,
I'm working with gamm models of this sort:
gm<- gamm(Z~te(x,y),data=DATA,random=list(Group=~1))
gm1<-gamm(Z~te(x,y,by=Factor)+Factor,data=DATA,random=list(Group=~1))
with a dataset of about 70000 rows and 110 levels for Group
if I use plot(gm1$gam), I obtain 3 different surface plots, one for each level of my factor but I would like to create more complex contour plots for those 3
2010 Aug 05
1
plot points using vis.gam
Hello,
I'm trying to illustrate the relationships between various trait and
environment data gathered from a number of sites. I've created a GAM to do
this: gam1=gam(trait~s(env1)+s(env2)+te(env1,env2)) and I know how to create
a 3D plot using vis.gam. I want to be able to show points on the 3D plot
indicating the sites that the data came from. I can do this on a 2D plot
when there is one
2006 Nov 14
2
Matrix-vector multiplication without loops
Hi,
I am trying to do the following computation:
p <- rep(0, n)
coef <- runif(K+1)
U <- matrix(runif(n*(2*K+1)), n, 2*K+1)
for (i in 0:K){
for (j in 0:K){
p <- p + coef[i+1]* coef[j+1] * U[,i+j+1]
} }
I would appreciate any suggestions on how to perform this computation
efficiently without the "for" loops?
Thank
2006 Sep 29
2
X-axis labels in histograms drawn by the "truehist" function
Hi,
I have a simple problem that I would appreciate getting some tips. I am
using the "truehist" function within an "apply" call to plot multiple
histograms. I can't figure out how to get truehist to use the column names
of the matrix as the labels for the x-axis of the histograms.
Here is a simple example:
X <- matrix(runif(4000),ncol=4)
colnames(X)
2010 Feb 28
1
Which system.time() component to use?
Hi,
The `system.time(expr)' command provide 3 different times for evaluating the expression `expr'; the first two are user and system CPUs and the third one is total elapsed time. Suppose I want to compare two different computational procedures for performing the same task, which component of `system.time' is most meaningful in the sense that it most accurately reflects the
2011 Feb 18
2
How to flag those iterations which yield a warning?
Hi,
I am running a simulation study with the survival::coxph. Some of the simulations result in problematic fits due to flat partial likelihood. So, you get the warning message:
Warning message:
In fitter(X, Y, strats, offset, init, control, weights = weights, ... :
Loglik converged before variable 2 ; beta may be infinite.
How can I keep track of the simulations which yield any kind of
2006 Nov 29
2
How to solve differential equations with a delay (time lag)?
Hi,
I would like to solve a system of coupled ordinary differential equations,
where there is a delay (time lag) term. I would like to use the "lsoda"
function "odesolve" package. However, I am not sure how to specify the
delay term using the syntax allowed by odesolve.
Here is an example of the kind of problem that I am trying to solve:
> library(odesolve)