Displaying 20 results from an estimated 326 matches for "stddev".
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stddef
2010 Aug 08
0
[LLVMdev] MmapAllocator
...little performance impact in
> either direction, so that's good:
>
> ### 2to3 ###
> 35.590589 -> 35.824554: 1.0066x slower
>
> ### bzr_startup ###
> Min: 0.157976 -> 0.155976: 1.0128x faster
> Avg: 0.167575 -> 0.168924: 1.0081x slower
> Not significant
> Stddev: 0.00334 -> 0.00716: 2.1463x larger
> Timeline: http://tinyurl.com/39thymp
>
> ### call_method ###
> Min: 0.878663 -> 0.884666: 1.0068x slower
> Avg: 0.887148 -> 0.888667: 1.0017x slower
> Not significant
> Stddev: 0.02062 -> 0.02074: 1.0058x larger
> Timeline:...
2010 Aug 08
4
[LLVMdev] MmapAllocator
...ed tests. It
seems using mmap()/munmap() has very little performance impact in
either direction, so that's good:
### 2to3 ###
35.590589 -> 35.824554: 1.0066x slower
### bzr_startup ###
Min: 0.157976 -> 0.155976: 1.0128x faster
Avg: 0.167575 -> 0.168924: 1.0081x slower
Not significant
Stddev: 0.00334 -> 0.00716: 2.1463x larger
Timeline: http://tinyurl.com/39thymp
### call_method ###
Min: 0.878663 -> 0.884666: 1.0068x slower
Avg: 0.887148 -> 0.888667: 1.0017x slower
Not significant
Stddev: 0.02062 -> 0.02074: 1.0058x larger
Timeline: http://tinyurl.com/2fm39l2
### call_met...
2008 Jul 24
5
printa stddev error
Hi,
Searched for similar errors and nothing came up. Anybody know what this is?
When using aggregate stddev, and then trying to print it at END, using printa, I get this error:
dtrace: processing aborted: Invalid return value from callback
avg works fine. Tried on two recent builds of solaris (build 89 and build 94), on two difference sparc systems.
Here''s a sample script:
#!/usr/sbin/dtrace -F...
2013 Jun 24
5
[LLVMdev] [LNT] Question about results reliability in LNT infrustructure
...n we compare two testings, each of which is run with three samples, how would LNT show whether the comparison is reliable or not?
I have seen that the function get_value_status in reporting/analysis.py uses a very simple algorithm to infer data status. For example, if abs(self.delta) <= (self.stddev * confidence_interval), then the data status is set as UNCHANGED. However, it is obviously not enough. For example, assuming both self.delta (e.g. 60%) and self.stddev (e.g. 50%) are huge, but self.delta is slightly larger than self.stddev, LNT will report to readers that the performance improveme...
2011 Jun 08
1
using stimulate(model) for parametric bootstrapping in lmer repeatabilities
...dual level for consistency analysis, A-D are
other fixed and random effects that I have to control for.
Following Nakagawa and Scheilzeth I can work out the repeatability
estimate using the following (as it is a binomial and the residual
variance is fixed at 1).
attr(lme4::VarCorr(model)$E, "stddev")^2 /
(1*(pi^2)/3 + attr(lme4::VarCorr(model)$E, "stddev")^2 +
attr(lme4::VarCorr(model)$C, "stddev")^2 +
attr(lme4::VarCorr(model)$D, "stddev")^2 )
My question is can I use stimulate(model) to generate values that I
can then use to do parametric bootstrap ana...
2005 May 05
6
Need some quick help with lattice - barchart
...s.data.frame(t(structure(c(
1,2005,9.24,6.18,634,
2,2005,8.65,6.05,96,
8,2004,6.81,6.51,16,
9,2004,9.0,7.29,8,
10,2004,8.84,6.18,524,
11,2004,8.54,6.35,579,
12,2004,9.97,6.3,614,
12,2005,8.75,5.84,32,
), .Dim=c(5,8))))
colnames(testdata) <- c('month', 'year', 'mean','stdDev','miceCount')
testdata$month <- as.numeric(testdata$month)
testdata$year <- factor(testdata$year)
testdata <- testdata[do.call("order", testdata), ]
png('lexstar_3241.png', width=600, height=as.numeric(length(levels(testdata$year))*200), pointsize=8)
trellis....
2011 Jan 19
2
VarCorr
I have a loop that I would like to use to extract the "stddev" for
each itteration so I can average the "stddev" for all the runs. It
would be helpful to know how to extract the "stddev" for each run from
the VarCorr. Thanks
MCruns<-1000
sighatlvec<-rep(NA,MCruns)
sighatbvec<-rep(NA,MCruns)
sighatevec<-rep(NA,MCruns)
for...
2013 Jun 27
0
[LLVMdev] [LNT] Question about results reliability in LNT infrustructure
...two testings, each of which is run with three samples, how would LNT show whether the comparison is reliable or not?
>
>
> I have seen that the function get_value_status in reporting/analysis.py uses a very simple algorithm to infer data status. For example, if abs(self.delta) <= (self.stddev * confidence_interval), then the data status is set as UNCHANGED. However, it is obviously not enough. For example, assuming both self.delta (e.g. 60%) and self.stddev (e.g. 50%) are huge, but self.delta is slightly larger than self.stddev, LNT will report to readers that the performance improveme...
2006 Jul 03
1
gamm
...ly the intercept that is changing?
And where can I find some explanation on the magic output below?
Thanks
Piet
summary(b2$lme)
Random effects:
Formula: ~Xr.1 - 1 | g.1
Structure: pdIdnot
Xr.11 Xr.12 Xr.13 Xr.14 Xr.15 Xr.16 Xr.17 Xr.18
StdDev: 1.680679 1.680679 1.680679 1.680679 1.680679 1.680679 1.680679 1.680679
Formula: ~Xr.2 - 1 | g.2 %in% g.1
Structure: pdIdnot
Xr.21 Xr.22 Xr.23 Xr.24 Xr.25 Xr.26 Xr.27 Xr.28
StdDev: 1.57598 1.57598 1.57598 1.57598 1.57598 1.57598 1.57598 1.57598
Formula: ~Xr.3 - 1 | g...
2009 Aug 17
3
Newbie question re stddev, quantmod and performanceanalytics
...trying to calculate the std dev of returns of YHOO so far i got:
getSymbols("YHOO")
retYHOO <- Return.calculate(Cl(YHOO))
> sd(retYHOO)
YHOO.Close
NA
but i received an NA....can any assist? tks!
--
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2013 Jul 01
0
[LLVMdev] [LNT] Question about results reliability in LNT infrustructure
...two testings, each of which is run with three samples, how would LNT show whether the comparison is reliable or not?
>
>
> I have seen that the function get_value_status in reporting/analysis.py uses a very simple algorithm to infer data status. For example, if abs(self.delta) <= (self.stddev * confidence_interval), then the data status is set as UNCHANGED. However, it is obviously not enough. For example, assuming both self.delta (e.g. 60%) and self.stddev (e.g. 50%) are huge, but self.delta is slightly larger than self.stddev, LNT will report to readers that the performance improveme...
2018 Sep 20
2
Vectorization width not correct using #pragma clang loop vectorize_width
...th(32)
but i m getting width 8 for the following kernel;
#define M 128
#define N 128
#define SQRT_FUN(x) sqrtf(x)
int main(int argc, char** argv)
{
/* Variable declaration/allocation. */
double float_n = (double)N;
double data[N*M];
double corr[M*M];
double mean[M];
double stddev[M];
uint32_t i,j,k;
/*Initialize array(s). */
#pragma clang loop vectorize_width(1) //no vectorize
for (i = 0; i < N*M; i++)
{
data[i] = (50.0)*i;
}
kernel_1:
#pragma clang loop vectorize_width(32)
for (j = 0; j < M; j++)
{
mean[j] = 0.0;...
2012 Mar 21
1
AIC models are not all fitted to the same number of observation
...)
Both have the same number of observations and groups:
lmez6
Linear mixed-effects model fit by REML
Data: ika_z6_test
Log-restricted-likelihood: -2267.756
Fixed: lepus ~ vulpes
(Intercept) vulpes
1.35017117 0.04722338
Random effects:
Formula: ~1 | troncon
(Intercept)
StdDev: 0.8080261
Formula: ~1 | an %in% troncon
(Intercept) Residual
StdDev: 1.086611 0.4440076
Number of Observations: 1350
Number of Groups:
troncon an %in% troncon
169 1350
> lmez60
Linear mixed-effects model fit by REML
Data: ika_z6_test...
2009 Mar 05
1
[PATCH] OCFS2: Pagecache usage optimization on OCFS2
...time taken by event execution: 989.1867
per-request statistics:
min: 0.0000s
avg: 0.0066s
max: 0.4400s
approx. 95 percentile: 0.0417s
Threads fairness:
events (avg/stddev): 9375.0000/257.65
execution time (avg/stddev): 61.8242/0.01
-2.6.29-rc7-patched
Test execution summary:
total time: 71.9416s
total number of events: 150000
total time taken by event execution: 845.7592
per-request statistics:...
2001 Nov 14
2
lme: how to extract the variance components?
Dear all,
Here is the question:
For example, using the "petrol" data offered with R.
pet3.lme<-lme(Y~SG+VP+V10+EP,random=~1|No,data=petrol)
pet3.lme$sigma gives the residual StdDev.
But I can't figure out how to extract the "(intercept) StdDev",
although it is in the print out if I do "summary(pet3.lme)".
In S-plus3.4 , $var.ran is the estimate of the variance of the random
effects between clusters. what is the equivalent thi...
2007 Nov 27
2
lme object manipulation
...REML
Data: dat
Log-restricted-likelihood: 22.3213
Fixed: express1 ~ race * thaps + race * tuni
(Intercept) race thaps tuni race:thaps race:tuni
7.00034057 -0.02675202 -0.05687972 0.01265845 -0.03859781 -0.11248439
Random effects:
Formula: ~1 | fam
(Intercept)
StdDev: 0.1131353
Formula: ~1 | twin %in% fam
(Intercept)
StdDev: 0.1740635
Formula: ~1 | thaw %in% twin %in% fam
(Intercept) Residual
StdDev: 0.1177579 0.1182267
Variance function:
Structure: Different standard deviations per stratum
Formula: ~1 | race
Parameter estimates:...
2003 Mar 21
2
Trying to make a nested lme analysis
...to make this analysis using lme.
> model <- lme(Glycogen~Treatment, random=~1|Treatment/Rat/Liver)
> summary(model)
Linear mixed-effects model fit by REML
Data: NULL
AIC BIC logLik
233.6213 244.0968 -109.8106
Random effects:
Formula: ~1 | Treatment
(Intercept)
StdDev: 3.541272
Formula: ~1 | Rat %in% Treatment
(Intercept)
StdDev: 6.00658
Formula: ~1 | Liver %in% Rat %in% Treatment
(Intercept) Residual
StdDev: 3.764883 4.600247
Fixed effects: Glycogen ~ Treatment
Error in if (any(wchLv <- (as.double(levels(xtTab[, wchPval])) ==...
2007 Feb 25
1
nested design in lme, need help with specifying model
...-lme(Escape.parameter~Species, random=~1|Species/Replicate)
as I am interested in Species as fixed effects and want to know variability caused by Replicates nested within Species as random effects. However, when running this model, I get
Random effects:
Formula: ~1 | Species
(Intercept)
StdDev: 2.937479
Formula: ~1 | Replicate %in% Species
(Intercept) Residual
StdDev: 4.973931 4.266302
Fixed effects: Max_speed ~ Species
Value Std.Error DF t-value p-value
(Intercept) 23.792040 4.798143 39 4.958593 0
Spec2 -7.121766 6.747930 0 -1.05...
2003 Dec 10
0
nested analysis with lme - odd result?
...factor(F3f))
v <- as.numeric(VarCorr(y.lme)[,2])
v <- as.numeric(na.omit(v))
F1V <- c(F1V,v[1])
F2V <- c(F2V,v[2])
F3V <- c(F3V,v[3])
residV <- c(residV,y.lme$sigma)
}
var.df <- data.frame(F1V,F2V,F3V,residV)
par(mfrow=c(2,2))
hist(var.df$F1V,main='Level 1 StdDev')
hist(var.df$F2V,main='Level 2 StdDev')
hist(var.df$F3V,main='Level 3 StdDev')
hist(var.df$residV,main='Residual StdDev')
txt <- 'Simulated stddev:'
for (i in 1:length(simVar)) {
txt <- paste(txt,' level ',i,'=',simVar[i],',',sep...
2011 Mar 26
0
NetCDF - rolling means and StdDev
Hello,
I am trying to come up with a routine to calculate a rolling mean and
standard deviation for three parameters stored in a NetCDF file. The NetCDF
file contains 10 years of daily records for each of the three parameters,
and I need the statistics for each of the three parameters.
Below I include some code illustrating what I've done so far. Obviously this
approach does not get at the