similar to: Adding non-data line to legend ggplot2 Maximum Contaminant Level

Well, here is one way but it seems a bit clumsy. In words, I created a new data.frame with "250" in the Chloride vector and "SMCL" in the Detections vector and supplessed one legend. Warning: For my convenience I am using different data.frame names . library(ggplot2) MyData <-read.csv("http://doylesdartden.com/Stats/TimeSeriesExample.csv", sep=",")

I just glanced at the problem but I think you would have to create a new variable to replace the hline. What about adding some text annotation in the graph instead? On Tuesday, September 26, 2017, 3:51:46 PM EDT, David Doyle <kydaviddoyle at gmail.com> wrote: Hello everyone, I have a plot showing chloride concentrations for various point over time. I also have a dotted line that

Say I have a dataset that looks like Location Year GW_Elv MW01 1999 546.63 MW02 1999 474.21 MW03 1999 471.94 MW04 1999 466.80 MW01 2000 545.90 MW02 2000 546.10 The whole dataset is at http://doylesdartden.com/ExampleData.csv and I use the code below to do the graph but I want to do it without MW01. How can I

Reading in the data from the file x <- read.csv( "ExampleData.csv", header = TRUE, stringsAsFactors = FALSE ) Subsetting as you want x <- x[ x$Location != "MW01", ] This selects all rows where the value in column 'Location' is not equal to "MW01". The comma after that ensures that all columns are copied into the amended data.frame. Rgds,

Hi Folks, I'm looking to do Confidence bands around LOESS smoothing curve. If found the older post about using the Standard error to approximate it https://stat.ethz.ch/pipermail/r-help/2008-August/170011.html Also found this one http://www.r-bloggers.com/sab-r-metrics-basics-of-loess-regression/ But they both seem to be approximations of confidence intervals and I was wonder if there was

Hi R users, I'm here trying to understand correlated residuals in nonlinear estimation. I'm reading/studying the book Bates, D. M. and D. G. Watts, (1988), /Nonlinear regression analysis and its applications/, Wiley, NY. pages 92-94, trying to reproduce the figures and to find out the code in R to perform the necessary calculations. I also consulted Pinheiro and Bates, but without

Hi, We have 2 UPS Chloride 80 NET 120 ( a black and white one ) in our datacenter. Could you please tell me if it is possible to use upsmon or other free solution with these two UPS for shuting down servers during electrical lost power before battery crash . Beet regards, Roger -------------- next part -------------- An HTML attachment was scrubbed... URL:

Kevin Wright wrote: > library(nlme) > m2 <- gnls(conc ~ t1*(1-t2*exp(-k*time)), > data = df.Chloride, > start = list( > t1 = 35, > t2 = 0.91, > k = 0.22)) So my error was to use nls instead that gnls. Thanks a lot, Kevin. > summary(m2) > plot(m2) > lag.plot(resid(m2), do.lines=FALSE) >

Hello, I have some data covering contaminant concentrations in fish over a time period of ~35 years. Each year, multiple samples of fish were taken (with varying sample sizes each year). Ultimately, I want an estimation of the variance between years, and the variance within years + random effects. I used a linear mixed model to estimate these variances, but after reading a number of different

I don't find how to do what I need to do in Dalgaard or 'R Cookbook', so I'm asking here. I have a data frame with water chemistry data and I want to start exploring these data. There are three factors (site, date, chemical) associated with each measurement. The data frame looks like this: > summary(chemdata) site_id.sample_date.param.quant

Please use reply-all to keep the discussion on the list. On May 29, 2015, at 11:55 AM, Zena Bingani <rogerndo at gmail.com> wrote: > Hi, > > Yes my two 120 kva UPS ( Chloride 80 Net 120 ) are newer than the entry in the compatibility list. > > Their windows monitoring software is Chloride MopUps P/R. > > It uses these protocols : RCCMD ( that is more interesting )

Hi R experts, I'm attempting to run Linear Discriminant Analysis using the lda function in the MASS package. I've got around 50 predictor variables and one response variable. My response variable has 5 numeric categories that represent different clusters of fish abundance data (clusters were developed using Bray-Curtis and NMDS), and my predictor variables are environmental variables that

#is there a way to get NA in the table of descriptive statistics instead of the function stopping Thank you in advance #data x.f <- structure(list(Site = structure(c(9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L), .Label = c("BC", "HC", "RM119", "RM148", "RM179", "RM185",

I would like to add another axis on side 4 (see code below) #order the box plot any damn way I want too order1 <- factor(as.character(x$Site), levels=c("Betty's Branch", "Stevens Creek", "North Augusta", "520", "Horse Creek", "Stan's", "place","Downstream", "IP",

On Thu, May 28, 2015 at 11:56 AM, Zena Bingani <rogerndo at gmail.com> wrote: > Hi, > > We have 2 UPS Chloride 80 NET 120 ( a black and white one ) in our > datacenter. > > Could you please tell me if it is possible to use upsmon or other free > solution with these two UPS for shuting down servers during electrical lost > power before battery crash Unclear. There is

#the below code is the way that I would like the plot to look. I have tried to write a panel function: my.panel <- function(x, y, ..., pf = parent.frame()) { axis(side=1, at = seq(rng[1], rng[2], 1/12), labels = n, tcl = -0.3) } #but it does not work and I am at a loss and help would be appreciated. I will use this for multiple library(zoo) library(chron) #this is what I would like the

I am aware of the inherent risks of having plots with more than two axes, but I am trying to produce the graphs that I have been tasked with. That being said I am having a hard time figuring out how to have two axes onto a boxplot. below is the sample code. I would like BC on the plot produced with this code to be on a second axis with all of the others being on the first axis. This will be

Dear all, I?m analyzing this dataset containing biodiversity indices, measured over time (Week), and at various contaminant concentrations (Treatment). We have two replicates (Replicate) per treatment. I?m looking for the effects of time (Week) and contaminant concentration (Treatment) on diversity indices (e.g. richness). Initial analysis with GAM models showed temporal autocorrelation of

Hello, I own a Chloride Desk Power 650 UPS. It works with nut 2.2.2, megatec driver (serial cable), it still haven't tried the usb connection. It doesn't work with nut 2.0.4, because it doesn't answer to the "I" query (see megatec protocol). Product page: http://www.chloridepower.com/en/USA/Products/Technologies/UPSs2/Desk-Power/Overview2/ Regards, Cyril.

Dear all, I produced the following graph with ggplot which is almost fine, yet I don't like that the legend for "Means" and "Observations" includes a line, though no line is used in the plot for those two (the line for "Overall Mean" on the other hand is wanted): library(ggplot2) ddf <- data.frame(x = factor(rep(LETTERS[1:2], 5)), y = rnorm(10)) p <-