Displaying 20 results from an estimated 43 matches for "intervales".
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interval's
2007 Mar 31
1
add confidence intervales to xyplot for ANCOVA and extracting info
Hi,
I would like to add confidence intervales to an ANCOVA with 2
covariates when using xyplot.
What would be a good way of accomplishing this?
--8<---------------cut here---------------start------------->8---
rm(list = ls(all = TRUE))
rm(list = c(ls()))
library(lattice)
## 1. generate data
random <- rnorm(200)
y <- abs(random)...
2012 Aug 11
3
help counting in data
Hi
>i have this data
> X
[1] 5.79 1579.52 2323.70 68.85 426.07 110.29 108.29 1067.60 17.05
22.66
[11] 21.02 175.88 139.07 144.12 20.46 43.40 194.90 47.30 7.74
0.40
[21] 82.85 9.88 89.29 215.10 1.75 0.79 15.93 3.91 0.27
0.69
[31] 100.58 27.80 13.95 53.24 0.96 4.15 0.19 0.78 8.01
31.75
[41] 7.35 6.50
2008 Jul 29
0
Bootstraping GAMs for confidence intervales calculation
Dear R-Users,
I am resending this message just to reminder my question regarding the
calculation of a bootstrap confidence intervals for a GAM plot.
I am trying to apply a bootstrap to a GAM in order to calculate the 95%
confidence intervals for a smooth curve obtained by the ?plot.gam?
function of the mgcv package. Nonetheless, I am getting some
difficulties in transposing the results for
2011 Jan 14
1
one sided t test
Dear R,
I am using this R version:R version 2.11.1 (2010-05-31)(Cran Mirror Berlin)
It seems to me, that R constructs a wrong confidence intervall if you try to get a one sided t-test.
If the true mean is 1 and my alternative hypothesis (H1) says that mu is smaller ("less")than zero the conf. intervall should reach +∞ and not -∞ if it is constructed for the H0 saying that mu is
2010 Sep 21
1
Colorramp in Maptools, how to choose min and max values for the fg= argument
Hello,
I am using maptools for plooting geographical data.
The colour of the region indicates some region dependent value
(population for example).
I pass the colours of the regions to the plot.Map function by defining
the foreground colour:
jet.colors = colorRampPalette(c("#00007F", "blue", "#007FFF", "cyan",
"#7FFF7F", "yellow",
2012 May 08
2
Dividing tick-data into intervalls
Hi everybody, I am sorry that I am kind of spamming this forum, but I have searched for some input everywhere and cant really find a nice solution for my problem.
Data looks like:
price
2011-11-01 08:00:00 0.000000000
2011-11-01 08:00:00 0.000000000
2011-11-01 08:02:00 0.000000000
2011-11-01 08:03:00 -0.017033339
2011-11-01 08:13:00 0.000690001
2011-11-01
2011 Nov 24
2
Question on density values obtained from kde2d() from package MASS
Hello,
I am a little bit confused regarding the density values obtained from the function kde2d() from the package MASS because the are not in the intervall [0,1] as I would expect them to be. Here is an example:
x <- c(0.0036,0.0088,0.0042,0.0022,-0.0013,0.0007,0.0028,-0.0028,0.0019,0.0026,-0.0029,-0.0081,-0.0024,0.0090,0.0088,0.0038,0.0022,0.0068,0.0089,-0.0015,-0.0062,0.0066)
y <-
2009 Sep 02
6
Selftest intervall, APC Smart-UPS 750 RM
Hello
I recently switched from apcupsd to NUT2.2.2 without
any troubles.
I tried to figure out how I can configure the self-test
intervall. The command upsrw lists only the variables
battery.charge.low
battery.runtime.low
ups.delay.shutdown
ups.delay.start
The command usbhid-ups -D and the listing under
http://obsvermes.org/cgi-bin/nut/upsstats.cgi?host=apcsmart at localhost&treemode
2010 Jul 23
2
start and end times to yes/no in certain intervall
Hi List,
I have start and end times of events
structure(list(start = c("15:00", "15:00", "15:00", "11:00",
"14:00", "14:00", "15:00", "12:00", "12:00", "12:00", "12:00",
"12:00", "12:00", "12:00", "12:00", "12:00", "12:00",
2010 Sep 24
3
Odds ratio from Logistic model in R
Hi, I am new to R. Anyone can explain the following from R-help or
anyone can direct me how to calculate odds ratio from logistic model in
R. Thank you very much. Guoya
Stefano <stecalza at tiscalinet.it
<https://stat.ethz.ch/mailman/listinfo/r-help> > writes:
>Hi all.
>
>A simple question.
>Is there a function to compute the Odds Ratio and its confidence
intervall,
2015 Oct 23
1
Question about dovecot replication
Hi,
last week I installed 2 servers with two dovecot nodes and replication in active/active mode located in different datacenters.
Based on the howto from wiki "http://wiki2.dovecot.org/Replication" it works great.
According to the wiki it is recomended to run "doveadm purge" on both systems continously, because "doveadm purge" will not be replicated by the
2023 Apr 09
1
simultaneous confidence intervals for multinomial proportions: sample size
Hello!
I want to calculate simultaneous confidence intervals for a nominal variable with three categories: "yes", "no", "partially" and I expect that far more than 5 samples fall into each category.
I have read that Glaz & Sison's method is only appropriate for variables with 7 or more categories. Therefore, the Goodman method seems like a good idea.
I have
2001 Mar 05
1
Odds Ratio from Logistic Model
Hi all.
A simple question.
Is there a function to compute the Odds Ratio and its confidence intervall, from a logistic model (glm(.......,family=binomial....). I've written my own, but certainly someone did a better job.
Thank you in advance,
Stefano
***********************************************
Stefano Calza
Istituto di Statistica Medica e Biometria
Universit? degli Studi di Milano
Via
2001 Sep 27
1
cuts and breaks
Hi
I'm using the "image" function to produce a plot and I want to define
the breaks using "cut" and the colors using "heat.colors".
>
image(interp(mat2[,2],mat2[,1],mat2[,3]),breaks=cut(mat2[,3],30),col=heat.colors(29))
Error in image.default(interp(mat2[, 2], mat2[, 1], mat2[, 3]), breaks =
cut(mat2[, :
must have one more break than colour
The
2011 Jul 11
1
problem finding p-value for entropy in reldist package
Hi,
I am using the reldist package and having problems determining the p-value
for the entropy value from the reldist function. I am able to properly
determine the entropy value, but cannot figure out what function to use to
find the p-value. I have tried using rpy, rpluy (which provides p-values
for the polarization values) and investing the results from reldist().
Thus, far I cannot find the
2009 May 21
1
Negative value for adjustedRandIndex?
Hello,
I am a very new user to R so please have patience with me. :clap:
I am trying to evalute the "internal response" for a couple of different
cluster methods with the help of the AdjustedRandIndex, which is included in
the mclust package.
However, I do get a bit puzzled when I get a negative value as the value
should be in intervall of [0,1], am I correct? Have I done something
2012 Jul 14
1
Quantile Regression - Testing for Non-causalities in quantiles
Dear all,
I am searching for a way to compute a test comparable to Chuang et al.
("Causality in Quantiles and Dynamic Stock
Return-Volume Relations"). The aim of this test is to check wheter the
coefficient of a quantile regression granger-causes Y in a quantile range. I
have nearly computed everything but I am searching for an estimator of the
density of the distribution at several
2010 Mar 29
1
getting CI's for certain y of nls fitted curve
hello,
i managed to get CI's for my curve - but now I need the intervall for a
certain y point (y_tenth) of the curve..
can anyone help me with this?
#####data:
por<-data.frame(list(structure(list(run = structure(c(1L, 1L, 1L, 1L, 2L,
2L,
2L, 2L, 3L, 3L, 3L, 3L), .Label = c("1", "3", "4"), class = "factor"),
press = c(15, 21, 24, 29.5, 15, 21,
2007 Mar 05
4
Identifying last record in individual growth data over different time intervalls
Hi
I have a plist t which contains size measurements of individual plants,
identified by the field "plate". It contains, among other, a field
"year" indicating the year in which the individual was measured and the
"height". The number of measurements range from 1 to 4 measurements in
different years.
My problem is that I would need the LAST measurement. I only
2008 Nov 07
1
sapply and median, possible or not ?
Hello,
I have a list of data.frame
rowsplit : List of 15
$ (0,0.025] :'data.frame': 169 obs. of 7 variables:
$ (0.025,0.05]:'data.frame': 174 obs. of 7 variables:
$ (0.05,0.075]:'data.frame': 92 obs. of 7 variables:
$ (0.075,0.1] :'data.frame': 76 obs. of 7 variables:
$ (0.1,0.125] :'data.frame': 37 obs. of 7 variables:
$