search for: mechanist

...to want to do either more or less than what I want. Precisely, I have a 4-component outcome, y, and am fitting multinomial logistic regression with one predictor x. What I would like to find out is, is there a single nonlinear function f(x) which acts in place of the linear predictor x. There is a mechanistic reason to believe this is sensible. So I'd like to fit a model \eta_j = \beta_{ (j) 0 } + \beta_{ (j) x } f(x) where both the function f(x) and its scaling coefficients \beta_{ (j) x } are fit simultaneously. Here \eta_j is the linear predictor, the logodds of outcome j vs the reference outc...

...and the likelihood maximization by iterated filtering (MIF) method of Ionides, Breto, and King (PNAS, 103:18438-18443, 2006). Future support for a variety of other algorithms is envisioned. A working group of the National Center for Ecological Analysis and Synthesis (NCEAS), "Inference for Mechanistic Models", is currently implementing additional methods for this package. Simple worked examples are provided in the form of a vignette, "random_walk_example". The package is provided under the GPL. Contributions are welcome, as are comments, suggestions, examples, and bug repor...

...and the likelihood maximization by iterated filtering (MIF) method of Ionides, Breto, and King (PNAS, 103:18438-18443, 2006). Future support for a variety of other algorithms is envisioned. A working group of the National Center for Ecological Analysis and Synthesis (NCEAS), "Inference for Mechanistic Models", is currently implementing additional methods for this package. Simple worked examples are provided in the form of a vignette, "random_walk_example". The package is provided under the GPL. Contributions are welcome, as are comments, suggestions, examples, and bug repor...

...ng evidence of a thresholding step-function, e.g. below some velocity, % cover ranges from 0% to 100% (with no apparent relationship to velocity within this range of velocities), but above a certain "threshold" velocity, the % cover does not appear to exceed, say, 10%. There are good mechanistic reasons for believing there is a step function there, so I'm trying to determine the velocity position and significance of this threshold. I came up with the following approach, but I was hoping to find out if there is a more "standardized" way of doing this: 1) Give small vel...

Hi, I am using the rcs() function in the Design library to model non-linearity that is not well characterized by an otherwise mechanistic function. I am able to make the model 'available' to others through the excellent nomogram() function and the set of tables that it can create. However, I would like to present the model in an 'expanded' format-- probably what rcspline.restate() or latex.Design() produce on a mode...

...repetitions of that time-series. These counts are generally known to be Poisson distributed, and the 4 processes A(t), B(t), C(t) and D(t) are independent of each other. B. It appears on visual observation that the following relationship holds; and such a relationship would also be expected on mechanistic considerations. A(t) = B(t) + C(t) - D(t) We now want to test this hypothesis statistically. Because successive counts in the sequence are likely to be correlated, isnt it true that none of these methods are valid ? Perhaps for other reasons as well ? a)Doing a chi-squared test to see if t...

Hi I would like to fit a non-linear regression to the follwoing data: quantiles<-c(seq(.05,.95,0.05)) slopes<-c( 0.000000e+00, 1.622074e-04 , 3.103918e-03 , 2.169135e-03 , 9.585523e-04 ,1.412327e-03 , 4.288103e-05, -1.351171e-04 , 2.885810e-04 ,-4.574773e-04 , -2.368968e-03, -3.104634e-03, -5.833970e-03, -6.011945e-03, -7.737697e-03 , -8.203058e-03, -7.809603e-03, -6.623985e-03,

...Thanks for any comments, Marco Visser Comment: In Matlab the the dominant eigenvetor and eigenvalue of the described matrix are given as the sixth. Again no idea why. reference J. A. Powell, I. Slapnicar and W. van der Werf. Epidemic spread of a lesion-forming plant pathogen - analysis of a mechanistic model with infinite age structure. (2005) Linear Algebra and its Applications 298. p 117-140. ____________________________________________________________________________________Ready for the edge of your seat? Check out tonight's top picks on Yahoo! TV. [[alternative HTML...

...ge and derive knowledge of biological processes from large biological datasets (e.g., expression profiling, and other ?omics? sets). In this role, he/she will share accountability for achieving team goals focused on: * Drug target discovery * Early biomarker discovery * Pathway understanding and mechanistic insight Teams will consist of computational biologists, geneticists, statisticians and bioinformatics specialists. These statistician positions are unique in requiring a substantial working knowledge of biology. This is necessary in order to collaborate effectively with biologists in the des...

...and to a more diversified portfolio based on our clientele<http://www.epixanalytics.com/clients-of-epix-analytics.html>. Responsibilities: - Quantitative model framing, development, review and interpretation. Models will include probabilistic models and statistical models, as well as mechanistic simulation models. - Preparation of reports and peer-reviewed scientific articles - Facilitation of meetings and presentations to clients, both in oral and written form - Regular interactions with EpiX consultants and with clients Requirements: - PhD in a quantita...

...use the risk of wrong results in Y will have a low impact. If Y happened to have an impact of $500m, then a reasonable approach might be to reconsider and find an additional expert, say Doug B, to confirm. Alternatively, if you don't believe in expert opinions (or subjective probability, or mechanistic modeling), and feel like an empirical frequentist, you might just get a team of monkeys to verify that X in R seems correct, based on a project management strategy that incorporates someone's favorite IT risk mitigation approach. With respect to Bert's points about 21CFR Part 11, plea...

Hi R-listers, I have developed 47 GLM models with different combinations of interactions from 1 variable to 5 variables. I have manually made each model separately and put them into individual tables (organized by the number of variables) showing the AIC score. I want to compare all of these models. 1) What is the best way to compare various models with unique combinations and different number

Hello all, I would like to fit a mixed effects model, but my response is of the negative binomial (or overdispersed poisson) family. The only (?) package that looks like it can do this is glmm.ADMB (but it cannot run on Mac OS X - please correct me if I am wrong!) [1] I think that glmmML {glmmML}, lmer {Matrix}, and glmmPQL {MASS} do not provide this "family" (i.e. nbinom, or

Dear R-users, dear Ron I use pls from the pls.pcr package for classification. Since I need to know which variables are most influential onto the classification performance, what criteria shall I look at: a) B, the array of regression coefficients for a certain model (means a certain number of latent variables) (and: squared or absolute values?) OR b) the weight matrix RR (or R in the De

Forum, I'm a grad student in Civil Eng, took some Stats classes that required students learn R, and I have since taken to R and use it for as much as I can. Back in my lab/office, many of my fellow grad students still use proprietary software at the behest of advisers who are familiar with the recommended software (Statistica, @Risk (Excel Add-on), etc). I have spent a lot of time learning

I use lmer to fit a mixed effect model.It give some warnings.what does this warnings mean? and what should I do? > (fm2.mlm <- lmer(qd ~ edu + jiankang + peixun +hunyin + cadcj + age + age2 + sex + dangyuan + Comp.1 + Comp.2+trust.cz1 +(trust.cz1|commid), data = individual,na.action = "na.exclude",family="quasibinomial")) Generalized linear mixed model fit using PQL

I have a batch of data in each line of data contains three values, calcium score, age, and sex. I would like to predict calcium scores as a function of age and sex, i.e. calcium=f(age,sex). Unfortunately the calcium scorers have a very "ugly distribution". There are multiple zeros, and multiple values between 300 and 600. There are no values between zero and 300. Needless to say, the

I''ve spent hours researching the subject and have tried many test sequences in IRB, and rails console but I''m just having trouble making headway into what is probably a very easy subject. I understand arrays with at least 4 other languages but with Ruby I haven''t found a mental connection with how I can assign variables to arrays.. Take for example: def

I am trying to create a frequency distribution and I am a bit confused. Here are the commands I have entered: > data <- read.csv(file="40609_sortedfinal.csv",head=TRUE,sep=",") > NumberOfActionsByStatus = data$STATUS > NumberOfActionsByUser = data$ETS_LOGIN > NumberOfBidOffer = data$BID_OFFER > NumberOfActionsByUser.freq = table(NumberOfActionsByUser) >