Displaying 20 results from an estimated 100000 matches similar to: "tolerance intervals"
2008 Apr 13
2
prediction intervals from a mixed-effects models?
How can I get prediction intervals from a mixed-effects model?
Consider the following example:
library(nlme)
fm3 <- lme(distance ~ age*Sex, data = Orthodont, random = ~ 1)
df3.1 <- with(Orthodont, data.frame(age=seq(5, 20, 5),
Subject=rep(Subject[1], 4),
Sex=rep(Sex[1], 4)))
predict(fm3, df3.1, interval='prediction')
# M01 M01
2010 Mar 14
1
confidence intervals for non-linear regression
Dear all,
I am interested to calculate confidence interval for fitted values in general for non-linear regressions. Lets say we have y=f(x1,x2,..xN) where f() is a non-linear regression. I would like to calculate a confidence interval for new prediction f(a1,..,aN). I am aware of techniques for calculating confidence intervals for coeffiecients in specific non-linear regressions and with them
2002 Jun 12
1
confidence intervals
Hello,
I wonder if anyone has a function for calculating confidence intervals for
ratios. I have mortality rates calculated for several groups from sample
data -- but these can be treated as ratios?). I am entertaining the idea of
bootstrapping them.
Any help would be greatly appreciated.
TIA, Marwan
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2010 Sep 09
5
Calculating with tolerances (error propagation)
Hello Bernardo,
---------
If I understood your problem this script solve your problem:
q<-0.15 + c(-.1,0,.1)
h<-10 + c(-.1,0,.1)
5*q*h
[1] 2.475 7.500 12.625
---------
OK, this solves the simple example.
But what if the example is not that simple. E.g.
P = 5 * q/h
Here, to get the maximum tolerances for P, we need to divide the maximum
value for q by the minimum value for h, and
2017 Aug 16
1
Bias-corrected percentile confidence intervals
Hi folks,
I'm trying to estimate bias-corrected percentile (BCP) confidence
intervals on a vector from a simple for loop used for resampling. I am
attempting to follow steps in Manly, B. 1998. Randomization, bootstrap
and monte carlo methods in biology. 2nd edition., p. 48. PDF of the
approach/steps should be available here:
https://wyocoopunit.box.com/s/9vm4vgmbx5h7um809bvg6u7wr392v6i9
If
2009 Sep 09
1
Stats help with calculating between and within subject variance and confidence intervals
Hello.
I'm trying to find a way in R to calculate between and within subject
variances and confidence intervals for some analytical method
development data.
I've found a reference to a method in Burdick, R. K. & Graybill, F. A.
1992, Confidence Intervals on variance components, CRC Press. This
example is for Balanced Data confidence interval calculation from Pg
62. The data are
2010 Aug 16
2
When to use bootstrap confidence intervals?
Hello, I have a question regarding bootstrap confidence intervals.
Suppose we have a data set consisting of single measurements, and that
the measurements are independent but the distribution is unknown. If
we want a confidence interval for the population mean, when should a
bootstrap confidence interval be preferred over the elementary t
interval?
I was hoping the answer would be
2009 Mar 16
0
the effect of blocking on the size of confidence intervals - analysis using lme and lmer
This is a follow-up mail of "the effect of blocking on the size of
confidence intervals - analysis using aov".
In both mails I pursue the idea of using blocking factors in order to
reduce the width of confidence intervals.
My dataset comprises,
a quantitative response variable, namely: "response", and
three categorical eplanatory variables, namely: "method",
2006 Dec 14
2
Extracting tolerance in R?
Dear list,
How is the tolerance for a model parameter in an lm() call extracted?
I did not see a solution in the documentation for lm(), or predict(), nor in the
archives using 'tolerance' as the search string. I also checked into the nlme
package, though nothing popped out at me.
Sincerely,
KeithC.
2019 Dec 27
1
"simulate" does not include variability in parameter estimation
On 2019-12-27 04:34, Duncan Murdoch wrote:
> On 26/12/2019 11:14 p.m., Spencer Graves wrote:
>> Hello, All:
>>
>>
>> ? ????? The default "simulate" method for lm and glm seems to ignore the
>> sampling variance of the parameter estimates;? see the trivial lm and
>> glm examples below.? Both these examples estimate a mean with formula =
>>
2003 Apr 18
2
prop.test confidence intervals (PR#2794)
Full_Name: Robert W. Baer, Ph.D.
Version: 1.6.2
OS: Windows 2000
Submission from: (NULL) (198.209.172.106)
Problem: prop.test() does not seem to produce appropriate confidence intervals
for the case where the vector length of x and n is one. (I am not certain about
higher vector lengths.)
As an example, I include x=6 and n=42 which has a mean proportion of 0.115.
When I calculate the 95% CI
2010 Aug 10
1
one (small) sample wilcox.test confidence intervals
Dear R people,
I notice that the confidence intervals of a very small sample (e.g. n=6) derived from the one-sample wilcox.test are just the maximum and minimum values of the sample. This only occurs when the required confidence level is higher than 0.93. Example:
> sample <- c(1.22, 0.89, 1.14, 0.98, 1.37, 1.06)
> summary(sample)
Min. 1st Qu. Median Mean 3rd Qu. Max.
2010 Jul 21
1
"lmomRFA" package: error bounds/confidence intervals
Dear List
I?m using the ?lmomRFA? package to fit different distributions to my data
sample. To calculate the error bounds I used:
regsimq(?)
and
sitequantbounds(?)
So my questions are:
Are error bounds and confidence intervals the same thing?
And: Does
regsimq(? boundprob = c(0.05, 0.95))
calculate the 90 or the 95% confidence interval?
If error bounds and confidence intervals are
2009 Jan 09
2
rpart with interval censored data crashes R
Hi Everyone,
This example code results in R 'crashing'; that is the R application closes
with no warnings or error messages.
#-----------------------
myD <- read.table(stdin(), header=TRUE, nrows=20)
Broth Salt pH Temp N Y Growth
1 310 9.0 2.92 10 90.0 NA 0
2 615 6.0 7.82 30 1.0 2 1
3 217 2.0 7.34 10 7.0 8
2011 Jan 24
0
tolerance limits for nls predicted values
Greetings,
I would like to calculate tolerancelimits for a series of predicted values
from nonlinear regression models. I've been using the tolerance package
but the self-starting functions are not in the derivitive tables. When I
spellout the functions and supply starting values I repeatedly get an
error message regardless of the starting values I use (see output below).
Does anyone
2023 Nov 15
2
Cannot calculate confidence intervals NULL
R-Experts,
Here below my R code working without error message but I don't get the results I am expecting.
Here is the result I get:
[1] "All values of t are equal to 0.28611928397257 \n Cannot calculate confidence intervals"
NULL
If someone knows how to solve my problem, really appreciate.
Best,
S
#########################################################
# Difference in Spearman
2016 Apr 02
0
BCa Bootstrap confidence intervals
Dear R-Experts,
Thanks to Prof. Bonnett, I have got an R script working to calculate confidence intervals around the semipartial correlation coefficients.
Now, I would like to calculate BCa bootstrap CIs using the boot library and the boot.ci(results, type="all") function. How could I modify my R script (here below reproducible example) to get the BCa bootstrap CIs ?
CIsemipartcorr
2012 Oct 02
0
Possible error in BCa method for confidence intervals in package 'boot'
I'm using R 2.15.1 on a 64-bit machine with Windows 7 Home Premium.
Sample problem (screwy subscripted syntax is a relic of edited down a
more complex script):
> N <- 25
> s <- rlnorm(N, 0, 1)
> require("boot")
Loading required package: boot
> v <- NULL # hold sample variance estimates
> i <- 1
> v[i] <- var(s) # get sample variance
>
2013 Jan 30
2
How does predict() calculate prediction intervals?
For a given linear regression, I wish to find the 2-tailed t-dist
probability that Y-hat <= newly observed values. I generate prediction
intervals in predict() for plotting, but when I calculate my t-dist
probabilities, they don't agree. I have researched the issues with variance
of individual predictions and been advised to use the variance formula
below (in the code).
I presume my
2023 Nov 15
1
Cannot calculate confidence intervals NULL
I believe the problem is here:
cor1 <- cor(x1, y1, method="spearman")
cor2 <- cor(x2, y2, method="spearman")
The x's and y's are not looked for in data (i.e. NSE) but in the
environment where the function was defined, which is standard evaluation.
Change the above to:
cor1 <- with(d, cor(x1, y1, method="spearman"))
cor2 <- with(d, cor(x2, y2,