similar to: New R-Packages: Triangle and LHS

Hi I want to du a sensitivity analysis using Latin Hypercubes. But my parameters have to fulfill two conditions: 1) ranging from 0 to 1 2) have to sum up to 1 So far I am using the lhs package and am doing the following: library(lhs) ws <- improvedLHS(1000, 7) wsSums <- rowSums(ws) wss <- ws / wsSums but I think I can't do that, as after the normalization > min(wss) [1]

NIST maintains a repository of Statistical Reference Datasets at http://www.itl.nist.gov/div898/strd/. I have been working through the datasets to compare R's results to their references with the hope that if all works well, this could become a validation package. All the linear regression datasets give results with some degree of accuracy except one. The NIST model includes 11 parameters,

Hello everyone I am trying to get one of my packages through R's QC. The package is clean for me under R-2.4.1, R-2.5.0, and R-devel, but Kurt gets > > * checking R code for possible problems ... WARNING > hypercube: no visible binding for global variable ?f? Function hypercube() [cut-&-pasted below] is intended to return an adjacency matrix for an n-dimensional

Hello, I am performing a sensitivity analysis using a Latin Hypercube sampling. However, I have difficulty to draw a Hypercube sample for one variable. I?ve generated this variable from a Poisson distribution as follows: set.seed(5) mortality_probability <- round(ppois(seq(0, 7, by = 1), lambda = 0.9), 2) barplot(mortality_probability, names.arg = seq(0, 7, by = 1), xlab = "Age

I think you should take this conversation private or seek local statistical expertise. This is about strategies for analysis, not about programming in R. Cheers, Bert Bert Gunter "The trouble with having an open mind is that people keep coming along and sticking things into it." -- Opus (aka Berkeley Breathed in his "Bloom County" comic strip ) On Wed, May 31, 2017 at

Thank you very much Rob for your answer. I have some difficulties to understand how to apply my agent-based model to each parameter combination generated by the LHS, in particular when parameters are defined by probability distributions. Indeed, I have multiple parameters in my model: parameters which are defined by a single value (like ?temperature", "pressure?) and parameters which are

Hello, I got one question on the Latin hypercube sampling. suppose there are three variables a, b, c, all of them follow the normal distribution. the mean value and standard deviation for each are  a(32, 2), b(35,5), c(37,3). I would like to use Latin hypercube sampling to random generate 1000 samples. but it needs to satisfy the condition that a<b<c. How can I implement this

Hi all, I am a begginer in R and I have been trying to use the Conditioned Latin Hypercube to choose sample points only in areas close to roads due to the difficult thorough access in the study area. I could use a code to create the points throughout the area, but I need to create a code to make the R only comes up with points close to this road. I've been using the packages

My apologies, I forgot to CC: to the list on my previous communication with Daniel. Jesse ----- Forwarded by Jesse Albert Canchola/EMVL/DIAG/US/BAYER on 08/21/2006 10:50 AM ----- Jesse Albert Canchola/EMVL/DIAG/US/BAYER 08/21/2006 09:36 AM To "Daniel Nordlund" <res90sx5 at verizon.net> cc Subject RE: [R] Permutations with replacement Thanks, Daniel. I need to enumerate

Hi all, I am attempting to use latin hypercube sampling to sample different variable functions in a series of simultaneous differential equations. There is very little code online about lhs or clhs, so from different other help threads I have seen, it seems I need to create a probability density function for each variable function, and then use latin hypercube sampling on this pdf. So far, I

Thanks for your answer. I have attached the plot for representing the variable. I think that I need to draw a Hypercube sample for each age class (i.e., for 0, 1, 2, 3, 4, 5, 6, 7) in a given simulation (i.e., N = 1) and the LHS values for all age classes should be like the observed cumulative distribution (see attached figure). Thus, the output of randomLHS should be a matrix with 100 rows (N =

Thanks for your answer. However, my variable is simulated from the cumulative distribution function of the Poisson distribution. So, the pattern obtained from the function "qpois" is not the same as the observed pattern (i.e., obtained from the function "ppois") set.seed(5) mortality_probability <- round(ppois(seq(0, 7, by = 1), lambda = 0.9), 2)

I am attempting to use the R Commander Graphs Quantile-Comparison functionality on a dataset, to compare with a triangular distribution. I have the package triangle. My question is on the syntax of how to specify the parameters of the theoretical distribution in the Parameters field of the dialog box. For example, the theoretical distribution has min of 3000, max of 5000, mode of 4000. When

Hello, I would like to know if there's a package in R to solve the following problem: Let's consider a cloud of points in a n-dimensional space. Each point is associated to a specific value Vi (a real that can be positive or negative). I would like to find the n-dimensional hypercube that maximizes the sum of Vi corresponding to the points inside of the hypercube. How would you solve

>May 26, 2017; 11:41am Nelly Reduan Latin Hypercube Sampling when parameters are >defined according to specific probability distributions >Hello, > I would like to perform a sensitivity analysis using a Latin Hypercube Sampling (LHS). >Among the input parameters in the model, I have a parameter dispersal distance which is defined according to an exponential probability

Open Letter to Developers, Is there any way you can cut through the mob scene at Homeland Defense with a powerful new encryption/decryption formula? The government cryptography bunch are stuck in symmetry and asymmetry and are deaf/dumb/blind to supersymmetry. When it's so easy to line up a supersymmetrical hypercube fractal-to-fractal, pair-to-pair, quantum-to-quantum and slice through

Hi everybody, I'm trying to create a numerical data frame on which to perform PRCC. So far I have created a data frame that consists of function/vector output that displays in numerical form, but when I try and run PRCC (from epiR package) I get the following error message: "Error in solve.default(C) : Lapack routine dgesv: system is exactly singular" It appears this is because

> How can I draw a Hypercube sample for the variable mortality_probability so > that this variable exhibits the same pattern as the observed distribution? One simple way is to use the uniform random output of randomLHS as input to the quantile function for your desired distribution(s). For example: q <- randomLHS(1000, 3) colnames(q) <- c("A", "B",

Dear all, Does anybody have an idea or suggestion how to construct (plot) 4-dimensional hypercube in R. Thanks in advance for any pointers. Regards, Andrej

Hello all, I am trying to do a Latin Hypercube Sampling (LHS) to a 5-parameter design matrix. I start as follows: library(lhs) p1<-randomLHS(1000, 5) If I check the distribution of each parameter (column), they are perfectly uniformly distributed (as expected).For example, hist(p1[,1]) Now the hard (maybe strange) question. I want the combination of the first three parameters to sum up to