Hi
I looked in the help page which states
See Also
cor.test for confidence intervals (and tests).
cov.wt for weighted covariance computation.
Then I looked to cov.wt help page and it seems that it does what you want
cov.wt(data.frame(x,y), wt=c(.5,.25,.25), cor=T)
$cov
xy
x 1.1 4.1
y
Dear All,
I am trying to run simple code:
*UI.R*
library(shiny)
shinyUI(fluidPage(
titlePanel("Old Faithful Geyser Data"),
sidebarLayout(
sidebarPanel(
selectInput("gb","gb",names(data))
,
selectInput("var","var",names(data))
),
# Show a plot of the gene
Please consider the following R Script:
x = c(1,2,3)
y = c(1,2,9)
cor(x,y)
These three lines will produce, as I expected, the correlation between
the variables x and y. However, R is going to assume that the
probability that x = 1 is the same as the probability that x = 2.
> filter(any(c(abs(diff(as.Date(date))),NA)>31)& date == min(date))
Note that the 'date == min(date)' will cause superfluous output rows
when there are several readings on initial date for a given id/value
pair. E.g.,
> dat1 <- data.frame(stringsAsFactors=FALSE, id=rep("A", 4), value=rep("x", 4)
Trevor, Can I just check - were you using the new 'nb' from mgcv version
>= 1.8 or the old (and very slow) 'negbin' family? (Not that negative
binomial seems needed here, but just to know) best, Simon
On 16/07/14 21:16, Trevor Davies wrote:
Hi Simon,
Thank you so much for being active on thi
Hi Simon,
Thank you so much for being active on this list, it really is tremendously
helpful.
Thanks you for your insights, I was wondering whether both terms were
necessary.
As for 'NB wouldn't work' it was a convergence problem (and tremendously
slow). There were also issues with the models n
Ravi Varadhan jhu.edu> writes:
>
> Dear All,
> I am fitting a model for a binary response variable measured
> repeatedly at multiple visits. I am using the binomial GLMM using
> the glmer() function in lme4 package. How can I evaluate the model
> assumptions (e.g., residual diagnostics, adeq
Using base R you can solve this by doing some sorting and comparing
the first and last dates in each id-value group. Computing the last
and last dates can be vectorized.
f1 <- function(data) {
# sort by id, break ties with value, break remaining ties with date
sortedData <- data[with(data
Trevor,
It looks like you've added a parametric COR.YEARLY.MEAN in addition to
your s(cxe,cyn,by=COR.YEARLY.MEAN) term. Because the latter includes a
linear effect of COR.YEARLY.MEAN, then the parametric COR.YEARLY.MEAN
will not be identifiable, so gam has dropped it.
I guess from the scale
## Manuel,
## Please look at the maiz example in ?mmc in the HH package.
install.packages("HH") ## if necessary
library(HH)
?mmc
## After the full maiz example, then you need one more command
maiz.proj <- proj(maiz.aov)
maiz.proj
## I think you are looking for
maiz.proj$Within[, "Residuals"]
I have run a quasipoisson spatial model via GAM (NB just wouldn't work) and
I am getting the following output of one of my parameters
(COR.YEARLY.MEAN). Does this suggest an error in the model fit? The model
seems to have converged. Apologies for the lack of reproducible example
but it didn't rea
Dear All,
I am fitting a model for a binary response variable measured repeatedly at
multiple visits. I am using the binomial GLMM using the glmer() function in
lme4 package. How can I evaluate the model assumptions (e.g., residual
diagnostics, adequacy of random effects distribution) for a b
I was able to download it specifying the method as "curl", like this:
> download.file("http://www.nseindia.com/content/historical/DERIVATIVES/2014/JUL/fo09JUL2014bhav.csv.zip";,
> temp, method="curl")
#! Fábio
On Tue, Jul 15, 2014 at 3:46 PM, Electron Musketeer
wrote:
> Many thanks Ista. I wil
Hi,
If `dat` is the dataset
library(dplyr)
dat%>%
group_by(id,value)%>%
arrange(date=as.Date(date))%>%
filter(any(c(abs(diff(as.Date(date))),NA)>31)& date == min(date))
#Source: local data frame [3 x 3]
#Groups: id, value
#
# id date value
#1 a 2000-01-01 x
#2 c 2000-09-10 y
#3
Hello,
I'm having problems to analyse results from a RCB Design Experiment.I have
three blocks. For each block: four treatments (factor A), randomized. And for
each factor A treatment, I have 6 differents treatments (factor C), randomized.
myAOV=aov(response ~ factorA*factorC + Block + Error(
Hello,
I'm having problems to analyse results from a RCB Design Experiment.I have
three blocks. For each block: four treatments (factor A), randomized. And for
each factor A treatment, I have 6 differents treatments (factor C), randomized.
myAOV=aov(response ~ factorA*factorC + Block + Error(
You can show the 2 distributions at a given time with a simple plot
without needing to color in the areas. To show this change over time
you could use the animation package or faceting from the lattice or
ggplot2 packages (depending on how many time periods you have).
On Wed, Jul 16, 2014 at 9:41
Hello
I have a dialog (pasted below) that includes a couple of long listboxes
(require scrollbars). I want the display of the list to start at the
top, but by default the displayed portion of the list starts at the
selected position + 1 (or the first selected position +1 if extended
selection).
Hi Michael,
Thank you! Just to clarify, in my question, I was thinking that in this
regression each study should be treated as one point, instead of each
species, so that each effect size x value has a unique climate y value. Is
that what the random= list(~1|Species, ~1|Site) argument is doing?
T
Greg,
I think you encapsulate my dilemma well. I could produce a graph
using Excel in 5 minutes but they look so boring and lack precision.
A key benefit of R is the ability to produce quality customised graphs.
I have the books by Tufte and Cleveland and perhaps there is a
better way to portray
> Is there a way to produce good quality area graphs in R? If so I would greatly
> appreciate being directed to the relevant package or a code example.
Have you tried googling 'area plot in R'?
There's a geom_area feature in ggplot2 which probably meets most expectations
of 'high quality'. See
You ask: "Is there a way to produce good quality area graphs in R?" I
would modify that question a little and ask it back as:
Is there a way to produce good quality area graphs?
Consider the following:
> library(fortunes)
> fortune(197)
If anything, there should be a Law: Thou Shalt Not Even T
Hi Sarah,
Thank you.
What I’m looking for is similar but a a more refined example. The
stack poly example looks a bit nearer what I had in mind.
Kind regards
Graham
On 16 Jul 2014, at 14:58, Sarah Goslee wrote:
> You mean like this?
>
> http://stackoverflow.com/questions/10840314/stack
Also look at stackpoly() in the plotrix package.
The R Graphical Manual shows the example plots here
http://rgm.ogalab.net/RGM/R_rdfile?f=plotrix/man/stackpoly.Rd&d=R_CC
David Carlson
-Original Message-
From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org] On
Behalf
On Wed, Jul 16, 2014 at 8:51 AM, jim holtman wrote:
> I can reproduce what you requested, but there was the question about
> what happens with the multiple 'c-y' values.
>
>
>
>> require(data.table)
>> x <- read.table(text = 'id date value
> + a2000-01-01 x
> + a2000
Thanks guys - amazingly prompt solutions from the R community as always.
Yes, the c-y value reverts to just the first date event - the spirit of
this is that I am trying to identify and confirm a list of diagnoses that
a patient has coded in government administrative data. Once a diagnosis is
made
Thanks. So you only want a single entry with a given "id" & "value",
even if there are multiple possible confirmations.
Too bad about not being in an SQL data base. I've already partially
solved the problem using PostgreSQL. Just in case you, or others,
might be interested, below is a transcript o
You mean like this?
http://stackoverflow.com/questions/10840314/stacked-area-graph-in-r
http://menugget.blogspot.com/2013/12/data-mountains-and-streams-stacked-area.html
http://stackoverflow.com/questions/22544571/create-stacked-area-graph-from-time-data
Or any of the many other results from a go
I can reproduce what you requested, but there was the question about
what happens with the multiple 'c-y' values.
> require(data.table)
> x <- read.table(text = 'id date value
+ a2000-01-01 x
+ a2000-03-01 x
+ b2000-11-11 w
+ c2000-11-11 y
+ c2000-10-01
Area graphs are a commonly used graphic in such software as Excel but I have
been unable
to find any examples of their use using R.
Is there a way to produce good quality area graphs in R? If so I would greatly
appreciate
being directed to the relevant package or a code example.
Any help will b
On 14/07/2014, 11:42 AM, Fowler, Mark wrote:
> Hello,
>
>
>
> Two unrelated questions, and neither urgent.
>
>
>
> Windows 7, R 3.0.1. Using R Console, no fancy interface.
>
>
>
> The function help ultimately becomes lost to a session kept running for
> extended periods (days). I.e. wit
On Wed, Jul 16, 2014 at 8:07 AM, Williams Scott
wrote:
> Hi R experts,
>
> I have a dataset as sampled below. Values are only regarded as Œconfirmed¹
> in an individual (Œid¹) if they occur
> more than once at least 30 days apart.
>
>
> id date value
> a2000-01-01 x
> a2000-03-01 x
> b
Hi R experts,
I have a dataset as sampled below. Values are only regarded as Œconfirmed¹
in an individual (Œid¹) if they occur
more than once at least 30 days apart.
id date value
a2000-01-01 x
a2000-03-01 x
b2000-11-11 w
c2000-11-11 y
c2000-10-01 y
c2000-09-10 y
c
Hi Jim,
Lost the address (Tuesday night is a major system scan for DFO, messes
everybody up). Tried your suggestion, no luck. Also tried shutting down
all Explorer browsers, still no luck. Maybe something related to
configuration or environment differs between our systems.
-Original Message---
We are please to announce the following book:
Title: Beginner's Guide to GAMM with R.
Authors: Zuur, Saveliev, Ieno
Book website: http://www.highstat.com/BGGAMM.htm
Paperback, hardcover or EBook can be order (exclusively) from:
http://www.highstat.com/bookorder.htm
Table of Contents: http://
At 23:19 14/07/2014, Megan Bartlett wrote:
Thanks very much, Wolfgang and Michael! I feel like I understand rma much
more clearly.
But just to make sure, is there any way to do this kind of analysis for a
continuous predictor variable?
Yes, just put it in as a moderator.
I am not sure I fully
Thanks for all these indications
Regards
Ludovic Brossard
-Message d'origine-
De : Jeff Newmiller [mailto:jdnew...@dcn.davis.ca.us]
Envoyé : mercredi 16 juillet 2014 04:06
À : Ludovic.Brossard
Cc : Ludovic Brossard; r-help@r-project.org
Objet : Re: [R] request of information about creat
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