Displaying 20 results from an estimated 1000 matches similar to: "how to customize boxplot"
2007 Dec 10
1
moving average and NA values
The S-plus function moving.ave(data, span = 2) calculates the moving
average, but it does not have an argument to tell it how to deal with
NA values, so it will return NA for all averages as shown below.
Is there an R or S moving average function which is able to omit some
NA values in the dataset?
In the simple sample shown below it would be possible to just remove
the rows with NA values. The
2001 Nov 25
2
Boxplots using percentiles?
The standard R boxplot appears to use quartiles to determine the height of
the rectangles and a range parameter - RNG - (default=1.5 I think) that
determines the length of the whiskers as <= RNG x Interquartile Range. Is
it possible to instead define the range as extending to the 95th percentile?
If so, how would this be done?
nb, I'm plotting multiple boxplots on a single chart so a
2011 Apr 17
3
Box plot with 5th and 95th percentiles instead of 1.5 * IQR: problems implementing an existing solution...
Hi all,
I'm just getting started with R and I would appreciate some help. I'm having
trouble creating a boxplot with whiskers at the 95th and 5th percentiles
instead of at 1.5 * IQR. I have read the relevant documentation, and checked
existing mails on this topic. I found a small modification that should work
: https://stat.ethz.ch/pipermail/r-help/2001-November/016817.html and tried
to
2005 Oct 18
1
A two-part question about box-percentile plots, bpplot(): (1) yaxt="n" doesn't seem to work (2) how to display mean values
Dear List,
I have a two-part question related to bpplot(), a box-percentile plot
function in the Hmisc package.
Take the example given in the Help for bpplot(), for instance.
(1) How does one set but not draw the y-axis? What I did was,
bpplot(... , yaxt="n"), but that apparently does not work (though it
works for boxplot()).
(2) How does one display the mean value of each variable
2004 Sep 01
1
AW: Looking for help in calculating percentiles
How do I calculate the 95th percentile when I know the 25th, the median and the 75th??
Thanks,
Harmony Tenney
[[alternative HTML version deleted]]
2008 May 16
1
Lattice box percentile plot
Dear Nabble.
I am trying to draw a box percentile plot with trellis using the panel in
Hmisc. I really want to colour the plots in. I can alter several of features
of the plot by changing the trellis par settings but I just can’t fill the
shape in.
Here is some example code which alters line colour and dot symbol:
require(lattice)
require(Hmisc)
2008 Feb 18
2
Custom Plot - means, SD & 5th-95th% (Plotmeans or Boxplot)?
Any help with this problem would be greatly appreciated:
I need to produce a custom plot i haven't come across in R. Basically, I
want to show means, 1st standard deviation and 5th and 95th percentiles
visually, using something resembling a boxplot. Is it possible to completely
customize a boxplot so that it shows means as the bar (instead of, not as
well as medians), standard deviations at
2012 Nov 08
3
difference percentile R vs SPSS
Dear list,
I am calculating the 95th percentile of a set of values with R and with SPSS
In R:
> normal200<-rnorm(200,0,1)
> qnorm(0.95,mean=mean(normal200),sd=sd(normal200),lower.tail =TRUE)
[1] 1.84191
In SPSS, if I use the same 200 values and select Analyze -> Descriptive Statistics -> Frequencies
and under "Statistics", I type in '95' under Percentiles,
2004 Aug 31
4
More efficient matrix computation
I have a 20x3 matrix as follows:
> m <- replicate(3, matrix(rnorm(20),20,1))
I need to compute, say, 95th and 99th percentiles of
each column such that the resulting matrix becomes 2x3
with each row representing the respective percentile.
My "best effort" is to compute one column at a time as
follows:
> quantile(m[,1], c(0.95, 0.99))
To do the same for columns 2 and 3, I
2010 Jan 15
5
panel.bpplot
Hi everybody,
I am a newbie in R. I would like to use the panel.bpplot function on my data
set but I have some problems. Can this function work on matrix? My data set
have some NaN and when I run panel.bpplot function it returns error due to
the presence of NaN. How Can I solve this?
Thank you so much for your help
netrunner
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2002 Jul 18
1
boxplot $conf
Hello R-Help,
Could anybody tell me how the boxplot-function calculates the upper
and
lower extremes of the notch contained in $conf which I assume is the
confidence interval? Is it reliable for data which is not normally
distributed? If not, how can I calculate and boxplot a specific
confidence interval for not normally distributed data in R (increasing
the sample size does not normalize the
2008 Jun 13
2
Quartile regression question
I have data that looks like
lake,loglength,logweight
1,2.369215857,1.929418926
1,2.426511261,2.230448921
1,2.434568904,2.298853076
1,2.437750563,2.298853076
1,2.442479769,2.230448921
1,2.445604203,2.356025857
...
102,2.722633923,3.310268367
102,2.781755375,3.502153893
102,2.836324116,3.683407299
102,2.802773725,3.583312152
102,2.790285164,3.546419267
102,2.806179974,3.599118565
2011 Mar 27
1
Bootstrap 95% confidence intervals for splines
There appear to be reports in the literature that transform continuous
independent variablea by the use of splines, e.g., assume the dependent
variable is hot dogs eaten per week (HD) and the independent variable is
waistline (WL), a normal linear regression model would be:
nonconfusing_regression <- lm(HD ~ WL)
One might use a spline,
confusion_inducing_regression_with_spline <- lm(HD
2004 Jan 22
3
adding mean to boxplot
I am a new and unexperienced user of R and got so far as to know how to produce
boxplots. I have no experience of messing with function code, so presently I do
not know how to create a boxplot with group means instead of group medians. If
somebody could help me either replace the median with the mean or superimpose
the mean onto the existing boxplot, it would be appreciated.
2010 Jan 28
2
Print lattice output to table?
I have beautiful box and whisker charts formatted with lattice, which is
obviously calculating summary statistics internally in order to draw the
charts. Is there a way to dump the associated summary tables that are being
used to generate the charts? Realize I could use tapply or such to get
something similar, but I have all the groupings and such already configured
to generate the charts. Simply
2011 Jun 02
2
shading in overlap between two ranges
I have 2 datafiles 'target' and 'observed' as shown below (I will gladly
email these 2 small files to whomever). X25. And X75. Indicate the
value of 25th and 75th-percentile of the target ('what should be') and
the observed ('what is'). The i.value is simply the month.
> target
X i.value X25. X75.
1 one.month 1 10.845225 17.87237
2
2008 Nov 10
1
Preparing data for display
I have a dataset of about 10^6 rows, each consisting of a timestamp,
several factors, a string, some integers, and some floats.
I'd like to graph this data in various ways, including straightforward
ones (how many events per week over the past year for each of 4 values
of some factor), some less straightforward. I've managed to do this
by brute force, but I'd like to learn how to do
2008 Aug 02
1
Memory Problems with a Simple Bootstrap - Part II
I have distilled my bootstrap problem down to this bit of code, which
calculates an estimate of the 95th percentile of 7500 random numbers drawn
from a standard normal distribution:
library(boot)
per95 <- function( annual.data, b.index) {
sample.data <- annual.data[b.index]
return(quantile(sample.data,probs=c(0.95))) }
m <- 10000
x <- rnorm(7500,0,1)
B <-
2010 Jun 24
4
OT: Bandwidth calculations
Hi,
I know some of you are very experienced as to the working of
networks. I wondered whether there is some accepted way of determining
bandwidth needs based on the network traffic over time. For example,
looking at the figures for the network traffic through the server
interface, we have hourly, daily and monthly figures. If everything
were linear, taking the hourly figure and dividing it by
2010 Apr 05
1
new to R, analysis of latency data
Hi,
I'd like to move from excel to R because our dataset are so large. Here's
what my data looks like:
Transaction Rate Run# Transaction Type Location Latency in
Seconds
10 1 Order
A 0
10 1 Order
B