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1
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1answer
102 views

How we can implement the result of maximum principle in our numerical optimization algorithm?

I have an algorithm (in R) that maximizes a convex function on a compact convex set in every iteration. Based on the maximum principle, I know that the maximima are only attained on the boundary. But ...
0
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0answers
24 views

Parameter estimation with RNetLogo : chosing estimation technique with both continuous and discrete parameters

I want to estimate parameters for an agent-based model in Netlogo using R and the RNetLogo ...
1
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0answers
31 views

Package for integration over non-rectangular region

I want to compute the expected value of a multivariate function f(x) wrt to dirichlet distribution. My problem is "penta-nomial" (i.e 5 variables) so calculating ...
2
votes
1answer
136 views

Is R or Matlab currently faster?

The most up-to-date performance benchmarks comparison between R and Matlab that I could find are several years out of date: 1 2 Is anyone aware of a more up-to-date comparison?
0
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2answers
46 views

What is 'SOLVER' in R and Statistics/Analytics ?

**strong text**a) I tried to research on what exactly is a SOLVER only to find a not clear-cut simple answer. My doubts still remain after going through several sites full of discussions about it. I ...
0
votes
1answer
35 views

Signal balancing using SVD: notations and implementation in R

Hibbs et. al use SVD to balance the strength of different underlying signals in gene expression data using the following decomposition: $X_{m*n} = U_{m*n} \Sigma_{n*n} V^T_{n*n}$ In this case $U$ ...
2
votes
1answer
147 views

How do I simultaneously minimize two different functions who have the same inputs?

I want to minimize two different functions simultaneously who have the same inputs. The functions are both linear and non-exponential. $$F_1(X_1, X_2) = a_1X_1 + a_2X_2$$ $$F_2(X_1, X_2) = b_1X_1 + ...
0
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1answer
268 views

computing the inverse of a large block diagonal sparse matrix in r

I would like to compute the inverse of some large block diagonal sparse matrix. The number of rows and columns is somewhat over 50,000. The blocks are 12 by 12 and are sparse (27 non zero elements). ...
1
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1answer
82 views

what went wrong with my logistic regression implementation in c++?

I have implemented a simple logistic regression function with IRLS algorithm using the armadillo linear algebra libray ...
2
votes
3answers
155 views

R/C/C++ library for N-dimensional arrays

I'm looking for a library that is either in R or easily wrappable with R, that can do the following things: construct and subset N-dimensional arrays perform operations such as ...
0
votes
1answer
3k views

why Lapack routine dgesv doesn't solve this?

Suppose I have the following 3 by 3 matrix: p<-3 X<-matrix(1/p,p,p) --$\pmb X$ is just a $p$ by $p$ matrix where every entry is $1/p$. Now I want to solve ...
0
votes
1answer
122 views

How could I implement this neural network in R? [closed]

In Establishing, versus maintaining, brain function: a neurocomputational model of cortical reorganisation after injury to the immature brain, Varier et al develop a neural network model of motor ...
6
votes
2answers
377 views

adaptive Gauss-Kronrod quadrature with vector-valued integrand

So I'm trying to implement a Gauss-Kronrod adaptive quadrature. That is, I want to calculate $$\int_a^b f(x) dx = \sum_i f(x_i) w_i$$ where f(x) is evaluated at multiple points at once for ...
3
votes
1answer
101 views

Constrained System / Combinatorial Problem

Let $x\in \mathbb{R}^{n}$, $Y\in \mathbb{R}^{mxn}$. We can then define: $row_{i}(Y)=$ $i^{th}$ row of $Y$ $column_{i}(Y)=$ $i^{th}$ column of $Y$ $x_{i}=i^{th}$ element of $x$ $sum(x)=$ sum of ...
0
votes
1answer
42 views

R language - how to list variables in use

How can I generate a list of all the variables that have been assigned in an R language session?
3
votes
1answer
161 views

LU Decomposition with memory-mapped matrices

I have a ~4.12 Tb structured relatively-sparse matrix dataset (about 8% of the matrix entries are non-zero) that i want to apply an LU decomposition, however, given the size of it, loading it in ...
0
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0answers
91 views

How to avoid over fitting? An application of GBM boosting package

I distributed my data into 90% training and 10% testing, then I build a boosting regression model using GBM boosting package in R which is very similar to the famous Adaboost regression model. There ...
12
votes
4answers
372 views

For which statistical methods are GPUs faster than CPUs?

I have just installed a Nvidia GT660 graphic card on my desktop and, after some struggle, I manage to interface it with R. I have been playing with several R packages that use GPUs, especially ...
3
votes
3answers
1k views

How to avoid NaN in optim?

Suppose, I have a function and want to optimize it. But if I use optim() which gives warnings(). How can I avoid these warnings ...
1
vote
1answer
109 views

Calculating AIC (in R or any other statistical software)

I am trying to fit the log-log plot of the cumulative distribution of a network to one of three models: Exponential (EXP) ($P(k)\sim e^{-ak}$), Exponentially truncated power law (TRU) ($P(k)\sim ...
4
votes
3answers
1k views

Storing a large, sparse array for R and Python

I've been working in R but sometimes switching to python. I'd like a more inter-language portable way of storing a large array than a csv file. (The particular csv file I'm dealing with is about 10^6 ...
5
votes
1answer
115 views

complexity constants in median computations same as that of general quantiles?

I would like to know whether the constant in the time complexity of computing the median is different from that of computing general quantiles. In R for example: ...