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Calculate mean squared error
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| calculate_mean_squared_error <- function(dati, samplesize, numberofbootstraps) | |
| { | |
| squared_error <- array(0, numberofbootstraps) | |
| mean_dati <- mean(dati) | |
| for(i in 1:numberofbootstraps) | |
| { | |
| squared_error[i] <- (mean_dati - mean(sample(dati, samplesize)))^2 | |
| } | |
| return(mean(squared_error)) | |
| } | |
| dati <- rnorm(800) | |
| samplesizes <- seq(10, 800, by=10) | |
| mean_squared_error <- array(0, length(samplesizes)) | |
| for(i in 1:length(samplesizes)) | |
| { | |
| cat(i, "\n") | |
| mean_squared_error[i] <- calculate_mean_squared_error(dati, samplesizes[i], 100) | |
| } | |
| plot(mean_squared_error ~ samplesizes) |
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