The hardware and bandwidth for this mirror is donated by dogado GmbH, the Webhosting and Full Service-Cloud Provider. Check out our Wordpress Tutorial.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]dogado.de.
#> Loading required package: greta#>
#> Attaching package: 'greta'#> The following objects are masked from 'package:stats':
#>
#> binomial, cov2cor, poisson#> The following objects are masked from 'package:base':
#>
#> %*%, apply, backsolve, beta, chol2inv, colMeans, colSums, diag,
#> eigen, forwardsolve, gamma, identity, rowMeans, rowSums, sweep,
#> tapply#> ℹ checking if python available#> ✔ python (v3.10) available#> #> ℹ checking if TensorFlow available#> ✔ TensorFlow (v2.15.0) available#> #> ℹ checking if TensorFlow Probability available#> ✔ TensorFlow Probability (v0.23.0) available#> #> ℹ checking if greta conda environment available#> ✔ greta conda environment available#> #> ℹ greta is ready to use!# simulate from a probabilistic 4-stage transition matrix model
k <- 4
# component variables
# survival probability for all stages
survival <- uniform(0, 1, dim = k)
# conditional (on survival) probability of staying in a stage
stasis <- c(uniform(0, 1, dim = k - 1), 1)
# marginal probability of staying/progressing
stay <- survival * stasis
progress <- (survival * (1 - stay))[1:(k - 1)]
# recruitment rate for the largest two stages
recruit <- exponential(c(3, 5))# combine into a matrix:
tmat <- zeros(k, k)
diag(tmat) <- stay
progress_idx <- row(tmat) - col(tmat) == 1
tmat[progress_idx] <- progress
tmat[1, k - (1:0)] <- recruit# analyse this to get the intrinsic growth rate and stable state
iterations <- iterate_matrix(tmat)
iterations$lambda#> greta array <operation>#> #> [,1]
#> [1,] ?#> #> greta array <operation>#> [,1]
#> [1,] ?
#> [2,] ?
#> [3,] ?
#> [4,] ?#> #> greta array <operation>#> [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13] [,14]
#> [1,] ? ? ? ? ? ? ? ? ? ? ? ? ? ?
#> [2,] ? ? ? ? ? ? ? ? ? ? ? ? ? ?
#> [3,] ? ? ? ? ? ? ? ? ? ? ? ? ? ?
#> [4,] ? ? ? ? ? ? ? ? ? ? ? ? ? ?
#> [,15] [,16] [,17] [,18] [,19] [,20] [,21] [,22] [,23] [,24] [,25] [,26]
#> [1,] ? ? ? ? ? ? ? ? ? ? ? ?
#> [2,] ? ? ? ? ? ? ? ? ? ? ? ?
#> [3,] ? ? ? ? ? ? ? ? ? ? ? ?
#> [4,] ? ? ? ? ? ? ? ? ? ? ? ?
#> [,27] [,28] [,29] [,30] [,31] [,32] [,33] [,34] [,35] [,36] [,37] [,38]
#> [1,] ? ? ? ? ? ? ? ? ? ? ? ?
#> [2,] ? ? ? ? ? ? ? ? ? ? ? ?
#> [3,] ? ? ? ? ? ? ? ? ? ? ? ?
#> [4,] ? ? ? ? ? ? ? ? ? ? ? ?
#> [,39] [,40] [,41] [,42] [,43] [,44] [,45] [,46] [,47] [,48] [,49] [,50]
#> [1,] ? ? ? ? ? ? ? ? ? ? ? ?
#> [2,] ? ? ? ? ? ? ? ? ? ? ? ?
#> [3,] ? ? ? ? ? ? ? ? ? ? ? ?
#> [4,] ? ? ? ? ? ? ? ? ? ? ? ?
#> [,51] [,52] [,53] [,54] [,55] [,56] [,57] [,58] [,59] [,60] [,61] [,62]
#> [1,] ? ? ? ? ? ? ? ? ? ? ? ?
#> [2,] ? ? ? ? ? ? ? ? ? ? ? ?
#> [3,] ? ? ? ? ? ? ? ? ? ? ? ?
#> [4,] ? ? ? ? ? ? ? ? ? ? ? ?
#> [,63] [,64] [,65] [,66] [,67] [,68] [,69] [,70] [,71] [,72] [,73] [,74]
#> [1,] ? ? ? ? ? ? ? ? ? ? ? ?
#> [2,] ? ? ? ? ? ? ? ? ? ? ? ?
#> [3,] ? ? ? ? ? ? ? ? ? ? ? ?
#> [4,] ? ? ? ? ? ? ? ? ? ? ? ?
#> [,75] [,76] [,77] [,78] [,79] [,80] [,81] [,82] [,83] [,84] [,85] [,86]
#> [1,] ? ? ? ? ? ? ? ? ? ? ? ?
#> [2,] ? ? ? ? ? ? ? ? ? ? ? ?
#> [3,] ? ? ? ? ? ? ? ? ? ? ? ?
#> [4,] ? ? ? ? ? ? ? ? ? ? ? ?
#> [,87] [,88] [,89] [,90] [,91] [,92] [,93] [,94] [,95] [,96] [,97] [,98]
#> [1,] ? ? ? ? ? ? ? ? ? ? ? ?
#> [2,] ? ? ? ? ? ? ? ? ? ? ? ?
#> [3,] ? ? ? ? ? ? ? ? ? ? ? ?
#> [4,] ? ? ? ? ? ? ? ? ? ? ? ?
#> [,99] [,100]
#> [1,] ? ?
#> [2,] ? ?
#> [3,] ? ?
#> [4,] ? ?#> #> ℹ 390 more values
#> Use `print(n = ...)` to see more values# Can also do this simultaneously for a collection of transition matrices
k <- 2
n <- 10
survival <- uniform(0, 1, dim = c(n, k))
stasis <- cbind(uniform(0, 1, dim = n), rep(1, n))
stay <- survival * stasis
progress <- (survival * (1 - stasis))[, 1]
recruit_rate <- 1 / seq(0.1, 5, length.out = n)
recruit <- exponential(recruit_rate, dim = n)
tmats <- zeros(10, 2, 2)
tmats[, 1, 1] <- stasis[, 1]
tmats[, 2, 2] <- stasis[, 2]
tmats[, 2, 1] <- progress
tmats[, 1, 2] <- recruit#> greta array <operation>#> #> [,1]
#> [1,] ?
#> [2,] ?
#> [3,] ?
#> [4,] ?
#> [5,] ?
#> [6,] ?
#> [7,] ?
#> [8,] ?
#> [9,] ?
#> [10,] ?#> #> greta array <operation>#> , , 1
#>
#> [,1] [,2]
#> [1,] ? ?
#> [2,] ? ?
#> [3,] ? ?
#> [4,] ? ?
#> [5,] ? ?
#> [6,] ? ?
#> [7,] ? ?
#> [8,] ? ?
#> [9,] ? ?
#> [10,] ? ?#> #> ℹ 10 more values
#> Use `print(n = ...)` to see more values#> [1] 10 2 100#> greta array <operation>#> #> , , 1
#>
#> [,1] [,2]
#> [1,] ? ?
#> [2,] ? ?
#> [3,] ? ?
#> [4,] ? ?
#> [5,] ? ?
#> [6,] ? ?
#> [7,] ? ?
#> [8,] ? ?
#> [9,] ? ?
#> [10,] ? ?#> #> ℹ 10 more values
#> Use `print(n = ...)` to see more values#> greta array <operation>#> #> , , 1
#>
#> [,1] [,2]
#> [1,] ? ?
#> [2,] ? ?
#> [3,] ? ?
#> [4,] ? ?
#> [5,] ? ?
#> [6,] ? ?
#> [7,] ? ?
#> [8,] ? ?
#> [9,] ? ?
#> [10,] ? ?#> #> ℹ 10 more values
#> Use `print(n = ...)` to see more valuesThese binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.