search for: stat_sum

...http://github.com/hadley/ggplot2 ggplot2 0.8.2 (2008-02-23) ---------------------------------------- New features * borders, fortify.map and map_data to make it easier to draw map borders and choropleth maps * cut_interval and cut_number utility functions to discretise continuous variables * stat_summary has reparameterised to make it easier to specify different summary functions. It now has four parameters: fun.y, fun.ymin and fun.ymax; and fun.data. See the documentation for stat_summary for more details Minor improvements * ggfluctuation: default to aspect ratio that produces squares * g...

...http://github.com/hadley/ggplot2 ggplot2 0.8.2 (2008-02-23) ---------------------------------------- New features * borders, fortify.map and map_data to make it easier to draw map borders and choropleth maps * cut_interval and cut_number utility functions to discretise continuous variables * stat_summary has reparameterised to make it easier to specify different summary functions. It now has four parameters: fun.y, fun.ymin and fun.ymax; and fun.data. See the documentation for stat_summary for more details Minor improvements * ggfluctuation: default to aspect ratio that produces squares * g...

Hi, I tried to do a nested Anova with the attached Data. My response variable is "survivors" and I would like to know the effect of (insect-egg clutch) "size", "position" (of clutch on twig) and "clone" (/plant genotype) on the survival of eggs (due to predation). Each plant was provided with three different sizes of clutches (45,15,5) and had

Let me start by introducing myself as a biologist with only a little knowledge about programming in matlab and R. In the past I have succesfully created my figures in matlab using the hist3d command, but I have not access to matlab right now and would like to switch to R. I have used the plot command to create a figure of my data and it does almost what I want it to do. My data matrix looks like

...very large bins * scale_discrete: factor levels no longer mistakenly reordered * scale_hue: now spans full range of hue if it less than 360 degrees * scale_hue: rotated default hue range by 15 degrees to avoid unfortunate red-green contrast in two colour case * show now works with ggplot objects * stat_sum: fixed bug which resulted in dropped aesthetics * stat_summary: now warns when dropping records with missing values * stat_summary: should be a little faster * stat_summary: correctly passes ... arguments on fun.data * theme_bw: corrected justification of axis.text.y * trans: bug fixes to logistic...

...very large bins * scale_discrete: factor levels no longer mistakenly reordered * scale_hue: now spans full range of hue if it less than 360 degrees * scale_hue: rotated default hue range by 15 degrees to avoid unfortunate red-green contrast in two colour case * show now works with ggplot objects * stat_sum: fixed bug which resulted in dropped aesthetics * stat_summary: now warns when dropping records with missing values * stat_summary: should be a little faster * stat_summary: correctly passes ... arguments on fun.data * theme_bw: corrected justification of axis.text.y * trans: bug fixes to logistic...

Hi there, I have been having trouble running negative binomial regression (glm.nb) using library MASS in R v2.15.0 on Mac OSX. I am running multiple models on the variables influencing the group size of damselfish in coral reefs (count data). For total group size and two of my species, glm.nb is working great to deal with overdispersion in my count data. For two of my species, I am getting a