search for: nitrogen

Hello, I have tried to find this out some other way, but unsuccessful I have to try this list. I assume this should be quite simple. I have a dataset with 4 columns, "Sample_no", "Species", "Nitrogen", "Carbon" in csv format. In the species column I have many different species with varying number of obs per species Eg "Sample_no" "Species" "Nitrogen" "Carbon" 1 Cod 15.2 -19.0 2 Haddock 14.8 -20.2 3 Cod 15.6 -18.5 4 Cod 13.2 -20...

I have no problem setting up my mixed model, or performing anova or lsmeans on my model?s outputs. However, performing lsd mean separation is giving me fits. So I do not have a problem when using two-way anova model. When using the code: fit.yield.add <- lm(data = ryzup, Yield ~ Rep + Nitrogen + Treatment) LSD.test(fit.yield.add, trt = "Nitrogen", alpha = 0.1, console = TRUE) It works beautifully. However when I run a mixed model: yield.lmer <- lmer(data = ryzup, Yield ~ Nitrogen + Treatment + (1|Rep/Nitrogen), REML = FALSE) LSD.test(yield.lmer, trt = "Nitrogen&...

Ben, I would like to test the sulfur on the clover field, nitrogen on the clover field and then test for the presence of interaction. Sorry about the last email, seems it really screwed itself over, here it is again, hopefully nicer: Nitrogen(0) Nitrogen(20) Sulfur(0) 4.54 5.73 Sulfur(3)...

What test do I use to determine if there is a correlation between a discrete variable and a continuous variable? For example - I have water quality ratings for streams (excellent, good, fair, poor) and a corresponding nitrogen concentration for each rating. I want to know if the the ratings correlate with the concentration of nitrogen in the stream. Help?

...reate internal c0t0d0 ./bonnie++ -d /internal/ -s 8g -u0 -f Version 1.03 ------Sequential Output------ --Sequential Input- --Random- -Per Chr- --Block-- -Rewrite- -Per Chr- --Block-- --Seeks-- Machine Size K/sec %CP K/sec %CP K/sec %CP K/sec %CP K/sec %CP /sec %CP nitrogen 8G 46916 18 27814 11 62103 8 212.5 0 ------Sequential Create------ --------Random Create-------- -Create-- --Read--- -Delete-- -Create-- --Read--- -Delete-- files /sec %CP /sec %CP /sec %CP /sec %CP /sec %C...

How do I set up my model equation in aov to analyze a split-plot design? I have two factors (CO2 and NITROGEN), each with two levels (high and ambient). CO2 is my whole-plot factor with three replicates for each level (i.e., 6 rooms total). Is this syntax below correct? summary(aov(response ~ ROOM + CO2*NITROGEN + Error(ROOM/CO2)))

> On 30 Sep 2017, at 14:22 , Robert Baer <rbaer at atsu.edu> wrote: > > > > On 9/29/2017 3:37 PM, Rolf Turner wrote: >> On 30/09/17 07:45, JLucke at ria.buffalo.edu wrote: >> >> <SNIP> >> >>> >>> The conceptual paradigm for R is only marginally commensurate with >>> that of >>> standard statistical

Hi, I am using the: pcf.aov<-aov(meas~op+part, data=pcf.ex2), command to perform a two way ANOVA. When I save the: sumpcf<- summary.aov(pcf.aov), result of the summary.aov command in a variable I need to access the individual pieces of information in the summary. The summary appears to be a list and I am having a hard time finding a way to get at the information in the summary.

when producing boxplot from bwplot, I have five groups: Nitrogen, Duration, Pressure, A, Z. I wish the graphical display is according to the original order. But the R-function bwplot seems to automatically adjust the groups according to the alphabetic oder and thus creat a graph for A, Duration, Nitrogen, Pressure and Z. How can I specify the original order in b...

LSD-test produces error for this code; code <- as.factor(Rotationdata_R$`Rot/code`) #factor in the main Nitrogen <- as.factor(Rotationdata_R$Nitrogen) #factor in the sub Rep <- as.factor(Rotationdata_R$REP) #blocks Year <- as.factor(Rotationdata_R$YEAR) #years model <- aov(Rotationdata_R$`GY(Mg/ha)`~Rep+code*as.factor(Nitrogen)+Error(Rep/Year/code),data=Rotationdata_R) summary(model) LSD.test(y...

On 9/29/2017 3:37 PM, Rolf Turner wrote: > On 30/09/17 07:45, JLucke at ria.buffalo.edu wrote: > > <SNIP> > >> >> The conceptual paradigm for R is only marginally commensurate with >> that of >> standard statistical software. >> You must immerse yourself in R to become proficient. > > Fortune nomination. For newer list members wondering what

...;libvirt-daemon-driver-nodedev-1.2.17-13.el7_2.4.x86_64 >libvirt-daemon-kvm-1.2.17-13.el7_2.4.x86_64 >[root@mdskvm-p01 ~]# cat /etc/release >cat: /etc/release: No such file or directory >[root@mdskvm-p01 ~]# cat /etc/*release* >NAME="Scientific Linux" >VERSION="7.2 (Nitrogen)" >ID="rhel" >ID_LIKE="fedora" >VERSION_ID="7.2" >PRETTY_NAME="Scientific Linux 7.2 (Nitrogen)" >ANSI_COLOR="0;31" >CPE_NAME="cpe:/o:scientificlinux:scientificlinux:7.2:GA" >HOME_URL="http://www.scientificlin...

...The following table has its clumns spaced closely so when I paste it to a word file it looks continuous. Is there any option in R to make the outputs like the second table? Any help will be highly appreciated. Thank you very much in advance. Model 1 4/70-3/80 Year 2 Source Area Runoff Nitrogen Phosphorus V1 LDR_imperv 203 52.6 1496.0 190.0 V2 LDR_perv 1147 5.7 489.6 163.6 V3 MDR_imperv 281 52.6 4141.7 654.7 V4 MDR_Perv 654 5.7 511.8 227.4 V5 IND_imperv 97 52.6 1604.4 226.0 V6 IND_perv 42 5.7 17.9 7.1 V7...

...4 >>> libvirt-daemon-kvm-1.2.17-13.el7_2.4.x86_64 >>> [root@mdskvm-p01 ~]# cat /etc/release >>> cat: /etc/release: No such file or directory >>> [root@mdskvm-p01 ~]# cat /etc/*release* >>> NAME="Scientific Linux" >>> VERSION="7.2 (Nitrogen)" >>> ID="rhel" >>> ID_LIKE="fedora" >>> VERSION_ID="7.2" >>> PRETTY_NAME="Scientific Linux 7.2 (Nitrogen)" >>> ANSI_COLOR="0;31" >>> CPE_NAME="cpe:/o:scientificlinux:scientificlinux:7....

Hi, we have a split-plot experiment in which we measured the yield of crop fields. The factors we studied were: B : 3 blocks I : 2 main plots for presence of Irrigation V : 2 plots for Varieties N : 3 levels of Nitrogen Each block contains two plots (irrigated or not) . Each plot is divided into two secondary parcels for the two varieties. Each of these parcels is divided into three subplots corresponding to three ordered levels of nitrogen. We found in Venables & Ripley (Modern Applied Statistics with S-...

Dear R colleagues: Am trying to fit a simple NL model to determine Economical Optimum Nitrogen Rates. The segmented (quadratic + plateau) model only works with some y's, in some cases I get a "singular gradient" error. I'll appreciate any ideas in how to solve the singular gradient error. Thanks, Jose # The following code works using yield2 in the nls model but not usi...

...rt-daemon-kvm-1.2.17-13.el7_2.4.x86_64 >>>> [root@mdskvm-p01 ~]# cat /etc/release >>>> cat: /etc/release: No such file or directory >>>> [root@mdskvm-p01 ~]# cat /etc/*release* >>>> NAME="Scientific Linux" >>>> VERSION="7.2 (Nitrogen)" >>>> ID="rhel" >>>> ID_LIKE="fedora" >>>> VERSION_ID="7.2" >>>> PRETTY_NAME="Scientific Linux 7.2 (Nitrogen)" >>>> ANSI_COLOR="0;31" >>>> CPE_NAME="cpe:/o:scientific...

The model should be class aov or lm and my model class is aovlist. tried tidy from broom library but did not work. To make it class aov, I had to remove the error term; model <- aov(Rotationdata_R$`GY(Mg/ha)`~Rep+code*as.factor(Nitrogen),data=Rotationdata_R) Ahmed Attia, Ph.D. Agronomist & Soil Scientist On Mon, Dec 25, 2017 at 7:38 PM, David Winsemius <dwinsemius at comcast.net> wrote: > >> On Dec 25, 2017, at 10:21 AM, Ahmed Attia <ahmedatia80 at gmail.com> wrote: >> >> LSD.test > &g...

On 04/12/2016 10:58 AM, TomK wrote: > Hey Martin, > > Thanks very much. Appreciate you jumping in on this thread. Can you provide some more details with respect to which libvirt version you have installed. I know I've made changes in this space in more recent versions (not the most recent). I'm no root_squash expert, but I was the last to change things in the space so that

Hello all, I have a data set where the response variable is the percent cover of a specific plant (represented in cover classes 0,1,2,3,4,5, or 6). This data set has a lot of zeros (plots where the plant was not present). I am trying to model cover class of the plant as a function of both total nitrogen and shrub cover. After quite a bit of research I have come across a conditional approach to modeling data with a lot of zeros (Fletcher et al. 2005, Welsh et al. 1996). In this approach you model the presence/absence data using a logistic regression and then model the presence only data using ord...