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Is there a function or an elegant way in the R language, to get the minimum range, that covers, say 95% of all values in a vector?
Any suggestions are very welcome :)
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95% of the values will be in the interval of (µ - 1.960 * stdev, µ + 1.960 * stdev).
We can find the range by performing the difference between the minimum value in the vector and the maximum value in the given vector. We can find maximum value using max() function and minimum value by using min() function. Example: R.
For this purpose, we can use quantile function in R. To find the 2.5th percentile, we would need to use the probability = 0.025 and for the 97.5th percentile we can use probability = 0.0975.
Create Quantiles of a Data Set in R Programming – quantile() Function. quantile() function in R Language is used to create sample quantiles within a data set with probability[0, 1]. Such as first quantile is at 0.25[25%], second is at 0.50[50%], and third is at 0.75[75%].
95% of the data will fall between the 2.5th percentile and 97.5th percentile. You can compute that value in R as follows:
x <- runif(100)
quantile(x,probs=c(.025,.975))
To get a sense of what's going on, here's a plot:
qts <- quantile(x,probs=c(.05,.95))
hist(x)
abline(v=qts[1],col="red")
abline(v=qts[2],col="red")
Note this is the exact/empirical 95% interval; there's no normality assumption.
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