search for: quantif

...ean. The heatmap is created for coordinate points of a location occupied by an animal, so the high density means the animal spent most of its time there, but what percentage of time? if is possible to get this out of the data and/or displayed more clearly in the legend? I addition, I would like to quantify the area size of the highest density region. Alternatively or in addition to this, I wouldn't mind measuring how many 'zones' the highest density region occupies. This might be more difficult, unless I can overlay a grid overtop of the data and count the number of zones covered. I have...

...e response variable is numeric. Some factors are important but others not. How to determine which categorical variables are significant to the response variable? Q2. As we knew, lm can deal with categorical variables. I thought, when there is a categorical predictor, we may use lm directly without quantifying these factors and assigning different values to factors would not change the fittings as shown: x <- 1:20 ## numeric predictor yes.no <- c("yes","no") factors <- gl(2,10,20,yes.no) ##factor predictor factors.quant <- rep(c(18.8,29.9),c(10,10)) ##quantificatio o...

...(like %recur, %det, trend, etc...) and that can be stored dynamically in a output file for all the 56 datasets. It seems that the function recurr does not calculate these parameters. Is there another function in the package that does so? If not, is there another package that deals with recurrence quantification analysis? I would be very glad to have this problem solved in R itself. Thanking in advance, Joy

...mals package http://www.jstatsoft.org/v31/i04 will get a major programming overhaul. This will take some time, but what's a few years on a 40-year project. Suggestions from the audience are welcome. homals() has a core loop over the m variables in which 1. tapply is used to compute category quantification (centroids) 2. category quantifications are then adjusted to satisfy the rank and level constraints The idea is to replace 1 by least squares fitting of a B-spline and to adjust 2 accordingly. The core will be re-programmed in C and/or FORTRAN (sometimes using existing routines), and the...

...mals package http://www.jstatsoft.org/v31/i04 will get a major programming overhaul. This will take some time, but what's a few years on a 40-year project. Suggestions from the audience are welcome. homals() has a core loop over the m variables in which 1. tapply is used to compute category quantification (centroids) 2. category quantifications are then adjusted to satisfy the rank and level constraints The idea is to replace 1 by least squares fitting of a B-spline and to adjust 2 accordingly. The core will be re-programmed in C and/or FORTRAN (sometimes using existing routines), and the...

...nts the distribution expected by chance. Within a Null Hypothesis Testing framework you then estimate the probability of the null by observing the proportion of simulated difference scores that are greater in magnitude than the observed difference score. Any guesses on how to translate this into a quantification of evidence? Mike -- Mike Lawrence Graduate Student Department of Psychology Dalhousie University Looking to arrange a meeting? Check my public calendar: http://tinyurl.com/mikes-public-calendar ~ Certainty is folly... I think. ~

...lly that would mean a plot with six different colours (next to white, which means no recurrence), rather than the plain black and white plot which does not reflect the nature of the recurrence. I hope that my explanation is clear enough. My procedure up until now has been: 1) perform a recurrence quantification analysis: testplot <- rqa(time.series = test$Code, embedding.dim = 1, time.lag = 1, radius = 0.1,lmin =2, vmin =2, distanceToBorder = 2, save.RM = TRUE, do.plot = TRUE) This plot is based on a TRUE FALSE sparse matrix. 2) Accordingly the next step was to transform th...

Dear useRs, I am using the gamm function in the mgcv package to model a smooth relationship between a covariate and my dependent variable, while allowing for quantification of the subjectwise variability in the smooths. What I would like to do is to make subjectwise predictions for plotting purposes which account for the random smooth components of the fit. An example. (sessionInfo() is at bottom of message) My model is analogous to > out.gamm &...

On Fri, Jul 31, 2015 at 6:18 PM, Reid Kleckner <rnk at google.com> wrote: > Consider this pseudo-IR and some possible transforms that I would expect to > be semantics preserving: > > void f(i32* readonly %a, i32* %b) { > llvm.assume(%a == %b) > store i32 42, i32* %b > } > ... > %p = alloca i32 > store i32 13, i32* %p > call f(i32* readonly %p,

...and developdiagnostic biomarkers as well as biomarkers for the characterization ofdisease models and drug effects ? including side effects. Essential functions * Analyzing omics data and integration of Metabolomics with other omics data-selection of likely metabolite, protein and RNA targets for quantification. * Providing software support for team members. * Contributing to presentations, patent applications, scientific publications and reporting on project funding. Requirements * Candidate can work independently and is highly motivated, creative and result-oriented. * Problem solving skills an...

...rd scaling, Benz?cri scaling, Goodman scaling, row-centroid, or column-centroid scaling. The summary method writes out a table with the chi-square (inertia) decomposition, it also writes out the singular values, and their asymptotic standard errors under multinomial sampling. Plots of the category quantifications (row scores and column scores) can be made optionally with asymptotic confidence ellipses, again based on multinomial sampling. The package contain various utilities to switch data formats, in particular to transform data frames to Burt matrices, to indicator matrices, and even to fuzzy in...

...a the q-form or s-form codes in NIfTI. Software development is currently under SourceForge via http://www.dcemri.org A mailing list has been established and feedback is appreciated. Functionality includes: Motion correction and co-registration via "fast template matching" T1 quantification via multiple flip-angle acquistions (inversion recovery coming soon!) Conversion to gadolinium contrast agent concentration Parametric models for the arterial input function (AIF), both literature-based (Tofts-Kermode and Fritz-Hansen) and data-adaptive. Kinetic parameter estimation using...

...plots) data(rtPCR) overplot( RQ ~ Conc..ug.ml. | Test.Substance, data=rtPCR, subset=Detector=="ProbeType 7" & Conc..ug.ml. > 0, same.scale=TRUE, log="xy", f=3/4, main="Detector=ProbeType 7", xlab="Concentration (ug/ml)", ylab="Relative Gene Quantification" ) # Error in lowess.default(mf[[-response]], mf[[response]], f = f, iter = iter, : # 'x' is empty # In addition: Warning messages: # 1: no non-missing arguments to min; returning Inf # 2: no non-missing arguments to max; returning -Inf ************************************...

...rd scaling, Benz?cri scaling, Goodman scaling, row-centroid, or column-centroid scaling. The summary method writes out a table with the chi-square (inertia) decomposition, it also writes out the singular values, and their asymptotic standard errors under multinomial sampling. Plots of the category quantifications (row scores and column scores) can be made optionally with asymptotic confidence ellipses, again based on multinomial sampling. The package contain various utilities to switch data formats, in particular to transform data frames to Burt matrices, to indicator matrices, and even to fuzzy in...

...a the q-form or s-form codes in NIfTI. Software development is currently under SourceForge via http://www.dcemri.org A mailing list has been established and feedback is appreciated. Functionality includes: Motion correction and co-registration via "fast template matching" T1 quantification via multiple flip-angle acquistions (inversion recovery coming soon!) Conversion to gadolinium contrast agent concentration Parametric models for the arterial input function (AIF), both literature-based (Tofts-Kermode and Fritz-Hansen) and data-adaptive. Kinetic parameter estimation using...

...espondence analysis, nonlinear principal component analysis, nonlinear multiset canonical correlation analysis. Implements everything in Gifi (1990) or SPSS Categories, and then some. Status: done. -- aspect package (optimizing functions of correlation matrices over transformations/quantifications of the variables -- functions implemented are sums of eigenvalues, determinants, multiple correlations, power sums). Status: done. -- optim package (miscellaneous optimization routines -- currently has pooled-adjacent-violaters for monotone regression and the hildreth-des...

...s working fine. below is the complete R code i am usign with the corresponding error, library(TCGAbiolinks) query.exp <- GDCquery(project = "TCGA-LUAD", data.category = "Transcriptome Profiling", data.type = "Gene Expression Quantification", workflow.type = "HTSeq - Counts", experimental.strategy = "RNA-Seq") query_load <- GDCdownload(query.exp) luad.exp <- GDCprepare(query = query.exp, save = TRUE, save.filename = "TCGA_LUAD_Exp.rda",...

...d develop diagnostic biomarkers, as well as biomarkers for the characterization of disease models and drug effects, including side effects. Essential functions * Analyzing omics data and integration of Metabolomics with other omics data- selection of likely metabolite, protein and RNA targets for quantification. * Contributing to presentations, patent applications, scientific publications and reporting on project funding. Requirements * Candidate can work independently and is highly motivated, creative and result-oriented. * Problem solving skills and strong team orientation are fundamental. * Go...

...the MD5 algorithm, which is often used with digital signatures...." There's more in the article cited above. Peace, david -- David H. Wolfskill david@catwhisker.org Evidence of curmudgeonliness: becoming irritated with the usage of the word "speed" in contexts referring to quantification of network performance, as opposed to "bandwidth" or "latency."

...lyse scatter plots and quantitatively differentiate between them. Since this is best demonstrated by a figure, I have attached one with 4 subfigures (a)-(d). Qualitatively (and I hope you would agree with me), sub-figures (a), (b), and (d) seem to represent uniform 2d scatters. It is hard for me to quantify it, but it seems as if the envelopes (max values of y-axis) are independent of the values of the x-axis. Sub-figure (c), on the other hand, exhibits a different behaviour, as the envelope seems to expand as the x-values increase (at least till some threshold, and with the exception of a single out...