| using Random, Distributions, Plots | |
| # the parent type | |
| abstract type ricker end | |
| # derived, concrete types | |
| mutable struct ricker_deterministic <: ricker | |
| x::Float64 | |
| r::Float64 | |
| k::Float64 |
| # a simple Ricker model, which may be stochastic if you provide `sd` or deterministic if not | |
| setup_ricker <- function(x0, r, k, sd = NULL) { | |
| type <- c("ricker") | |
| if (is.null(sd)) { | |
| type <- c(type, "ricker_deterministic") | |
| } else { | |
| type <- c(type, "ricker_stochastic") | |
| } | |
| mod <- structure(new.env(), class = type) | |
| mod$x <- x0 |
| fn_list <- function(y){ | |
| y$a <- y$a + 1 | |
| return(y) | |
| } | |
| fn_env <- function(y){ | |
| y$a <- y$a + 1 | |
| } | |
| x <- list(a=matrix(1:9,3,3),b=matrix(1:36,6,6)) |
| # for more info on comparing floats, this blog post is very informative: https://bitbashing.io/comparing-floats.html | |
| # for more info on how floating point mathematics compares to "real" mathematics, see https://www.tandfonline.com/doi/full/10.1080/10724117.2019.1611061 | |
| # helper function for approximate equality between floats | |
| approx_equal <- function(a, b, tol = sqrt(.Machine$double.eps)) { | |
| abs(a - b) <= tol | |
| } | |
| # use instead of the %in% operator to check if floats are in sets of other floats | |
| `%in_approx%` <- function(x, table) { |
| rm(list=ls());gc();dev.off() | |
| library(sna) | |
| set.seed(4395834L) | |
| n <- 100 | |
| w1<-rgraph(n) #Draw the AR matrix | |
| w2<-w1 #Draw the MA matrix | |
| x<-matrix(rnorm(n*5),n,5) #Draw some covariates | |
| r1<-0.2 #Set the model parameters |
| #include <functional> | |
| #include <Rcpp.h> | |
| // [[Rcpp::plugins(cpp14)]] | |
| using my_lambda = std::function<double(const double)>; | |
| typedef struct lambda_st { | |
| my_lambda func; |
| #include <random> | |
| #include <array> | |
| #include <iostream> | |
| #include <limits> | |
| #include <random> | |
| #include <Rcpp.h> | |
| // [[Rcpp::plugins(cpp14)]] |
| // Example program | |
| #include <iostream> | |
| #include <string> | |
| int main(void) { | |
| int arr[13] = {1, 2, 2, 123121, 123121, 3, 5, 6 , 7, 7, 14, 2, 16}; | |
| int len = 13; | |
| int unique[len]; |
Avery arrives at a coffee shop at a random time between 7:00 and 9:00, and Bruno at a random time between 6:00 and 10:00. The time one person arrives does not affect the other's.
Integrate[
PDF[UniformDistribution[{7, 9}], a + 0.5]*
PDF[UniformDistribution[{6, 10}], b], {b, 6, 10}, {a, 7, b}]