Home > Error Bars > R Lattice Plot Error Bars# R Lattice Plot Error Bars

## Lattice Error Bars

## Lattice Xyplot Error Bars

## For example, the following function call generates separate mean profiles for each diet and separate panels for each sibship.

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Alex van der Spek ______________________________________________ **[hidden email] mailing list https://stat.ethz.ch/mailman/listinfo/r-helpPLEASE** do read the posting guide http://www.R-project.org/posting-guide.htmland provide commented, minimal, self-contained, reproducible code. The panel.arrows function is just the lattice version of the arrows function of base graphics.The main new feature in this code is the use of the subscripts argument to the panel Today we focus on using base graphics and lattice to summarize ANOVA models. Can unconnected inputs make an IC get warm? http://caribtechsxm.com/error-bars/r-error-bars-lattice.php

E. 2000. This is especially useful if an appropriate reference group was chosen. This implies that the diet × Ru486 effect is no larger than effects attributable to ordinary background genetic variation. panel.groups="my.panel" identifies the group panel function that I created.

Just point to docs if avaiable. I change the color **of the profile to red,** col=2, and change the symbol type to open circles, pch=1. Browse other questions tagged r lattice standard-error or ask your own question. Related 41Lattice: multiple plots in one window?3plotting regression line in with lattice1Add text to lattice plot?1How to add median vertical line to panels of lattice density plot?0lattice, include error bars6Include lines

- In each data frame I add one more variable to indicate that fac3 level, fac3=1 or fac3=2.
- It is also possible to specify the location of the legend by explicitly giving the x- and y-coordinates of the top left corner of the legend.
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- One challenge I alwayshave is dealing with dates.
- This is denoted %*% in R and requires the use of the expression function. #formatted labels mylabs<-c('Normal', 'Ru486', 'Shrimp', 'Sibship2', expression('Normal' %*% 'Shrimp'), expression('Ru486' %*% 'Shrimp'), expression('Shrimp' %*% 'Sibship2')) To use

Notice that in the initial plot function I use all of the data to set the y-limits, not just the data for sibship 2. Terms and Conditions for this website Never miss an update! Thank you very much for your efforts in advance! Notice the ...

For instance, in the base graphics version of this plot I plotted the estimates in the mean profile for the shrimp diet twice, first using a white filled circle and the Lattice Xyplot Error Bars I’ll start with aline graph of the two treatment plot types. > ### Line Plot ### > # Ref: Quick-R > > # convert factor to numeric forconvenience > gCount$trtcode <-as.numeric(gCount$trt) This is also the role the notation x and y have in the function. I also take advantage of the mathematical typesetting abilities of R to include the multiplication symbol of arithmetic, ×, in the interaction terms.

Usage panel.errbars(x,y,...,panel.xy=panel.xyplot, make.grid=c("horizontal","vertical","both","none"),ewidth=0) Arguments x,y numeric values, the points around which error bars are plotted. Error t value Pr(>|t|) (Intercept) 3.38323831 0.05245374 64.4994720 1.024057e-149 fac1No 0.54729873 0.05837246 9.3759750 6.582616e-18 fac1Ru 0.53698650 0.06084917 8.8248782 2.755469e-16 fac2S 0.01714866 0.06696214 0.2560949 7.981054e-01 fac32 0.10757945 0.04814860 2.2343214 2.641948e-02 fac1No:fac2S 0.01341375 dotplot(var.labels~ests, data=new.data, xlim=c(min(new.data$lower95)-.02, max(new.data$upper95)+.02), xlab='Estimated effect', panel=function(x,y){ panel.dotplot(x, y, pch=16, cex=1.2, col='white') panel.segments(new.data$lower95, as.numeric(y), new.data$upper95, as.numeric(y),lty=1, col="black") panel.segments(new.data$lower50,as.numeric(y), new.data$upper50, as.numeric(y), lty=1, col="grey60", lwd=4) panel.xyplot(x, y, pch=16, cex=1.2, col='white') panel.xyplot(x, y, pch=1, The R doc is excellent.

It has modified it sufficiently that now in the left panel the diet effect is significantly different from zero at all three hormonal treatments (the confidence intervals fail to overlap). The data used represents intraoperative cardiovascular findings from patients undergoing surgery. Lattice Error Bars This means that the regression coefficients are multiplying terms that are either have value zero or one. Error Bars In R Grep lines before after if value of a string is greater than zero more hot questions question feed lang-r about us tour help blog chat data legal privacy policy work here

Because we're creating a single graph and not a panel, there is no particular reason to use the lattice package here. this page Most > of the time I can save myself. The argument **lty=3 causes** the grid lines to be dotted lines. For the text list I specify the vector of text that should appear in the legend and the size I want it to have.

We need to convert it to a dateform that R can recognize. legend('topleft', c('Detritus','Shrimp'), col=1:2, pch=c(16,1), cex=.8, pt.cex=.9, title=expression(bold('Food Type')),bty='n') The first argument of legend is the location of the legend in the plot. Free forum by Nabble Edit this page R › R help Search everywhere only in this topic Advanced Search Lattice: How to do error bars ‹ Previous Topic Next Topic › get redirected here I must saythat I like this.

I then reset the margins to their default values. The lattice package should be useful for this. > library(lattice) > > # Add year, month, and day todataframe > chardate <- as.character(gCount$date) > splitdate <- strsplit(chardate,split = "-") > gCount$year The lower level graphics functions of base graphics require the numeric values of the effect categories for plotting, so I just number them 1 through 7.

The R doc is excellent. xyplot(median ~ voice, groups=range, data=singer.ucl, ly = singer.ucl$lower, uy = singer.ucl$upper, The panel.superpose function in turn calls something called a panel.groups function that by default is panel.xyplot in which the points are colored separately by group. In this case switching to the shrimp diet has a weak positive effect, enough of an effect to make the Ru486 treatment significantly different from the corticosterone group, but not enough

For example, for a tadpole with sibship=1, diet=detritus, and hormone=Ru486 the effect is given by the single labeled estimate Ru486. used in function calls so that additional arguments are passed to that function as needed when that function is called %*% is the matrix multiplication operator in R R function options One solution to this is Sundar's > approach, which is to change the panel function to handle groups. > Another generic solution is to use 'panel.superpose', which _does_ > know how useful reference To make the point estimates more distinct I first draw them with a large filled white circle.

summary(out3)$coefficients Estimate Std. Can I search in the terminal window text? Magnusson, W. xyplot(est~fac1|factor(fac3), groups=fac2, data=fac.vals, type='b', col=c(1,2), pch=c(16,1), ylim=range(fac.vals[,'low95']-.1, fac.vals[,'up95']+.1), panel.groups="my.panel", panel="panel.superpose") ylim=range(fac.vals[,'low95']-.1, fac.vals[,'up95']+.1) decreases the minimum and increases the maximum y-limits a little bit to make room for the error bars.

The entire code for doing this is shown below. In addition I also pass to the group panel function the colors and plot characters I want it to use for the groups (the col and pch arguments in the function The left edge of the figure is x = 0 and the right edge of the figure corresponds to x = 1. new.data$var.labels2<-reorder(new.data$var.labels, new.data$ests) levels(new.data$var.labels) [1] "fac1No" "fac1Ru" "fac2S" "fac32" "fac1No:fac2S" [6] "fac1Ru:fac2S" "fac2S:fac32" levels(new.data$var.labels2) [1] "fac1No:fac2S" "fac2S" "fac32" "fac2S:fac32" "fac1Ru:fac2S" [6] "fac1Ru" "fac1No" Here reorder has created a new factor variable I

Next I tried thepopular package ggplot2. > ### ggplot ### > # Refs:http://learnr.wordpress.com/2010/02/25/ggplot2-plotting-dates-hours-and-minutes/ > # http://had.co.nz/ggplot2/ > #http://wiki.stdout.org/rcookbook/Graphs/Plotting%20means%20and%20error%20bars%20%28ggplot2%29 > > library(ggplot2) > > ggplot(data = gCount, aes(x = date,y = count, There are a couple of different functions that will take care of the details for you: xYplot() in the Hmisc package and segplot() in the latticeExtra package. -Deepayan ______________________________________________ [hidden email] r lattice standard-error share|improve this question asked Oct 13 '14 at 3:24 OFish 14314 What standard error do you want to plot exactly? Hocking >#################################################################### > > Data <- read.table(‘/Users/Dan/…/AllCountsR.txt',header = TRUE, na.strings = "NA") > > str(Data) ‘data.frame': 910obs.

To illustrate this, consider the singer data generated by the above linked solution previously submitted: ##################### library(lattice) singer.split <- with(singer, split(height, voice.part)) singer.ucl <- Code samples can be found at our GitHub repository. As is the norm with lattice, it is very easy to get a serviceable graph but much more difficult to get the exact graph you want. Probability smear graphs ANOVA models are regression models in which all the regressors are dummy variables.

Where an x or a y appear as an argument I replace it with an actual variable name. Specifying lty=1 yields a solid line, lty=2 is a dashed line, and lty=3 is a dotted line.