Method of Moments: Uniform Distribution

Approach

From Uniform Distribution, we know that the mean and the variance of the uniform distribution are (α + β)/2 and (β – α)2/12, respectively. Thus, x̄ ≈ (α + β)/2, and so β ≈ 2x̄ – α, from which it follows that

and so

Note that if we prefer to use the pure method of moments approach, then we need to substitute t for s in the above formulas.

Example

Example 1: Estimate the uniform distribution that fits the data in range B3:C12 of Figure 1.

Fit uniform distribution

Figure 1 – Fit for uniform distribution

We see from Figure 1 that the uniform distribution is over the interval [-.03587,1.0417]. In fact, the data in range B3:C12 was actually taken from the interval [0,1) using the formula =RAND(). There is also the possibility that there will be data elements outside the estimated interval.

Links

↑ Method of moments

Examples Workbook

Click here to download the Excel workbook with the examples described on this webpage.

References

Gong, Y. (2021) Method of moments
https://bookdown.org/yg484/lec_4_note/method-of-moments.html

Siegrist, K. (2022) The method of moments
https://stats.libretexts.org/Bookshelves/Probability_Theory/Probability_Mathematical_Statistics_and_Stochastic_Processes_(Siegrist)/07%3A_Point_Estimation/7.02%3A_The_Method_of_Moments

Wikipedia (2017) Continuous uniform distribution
https://en.wikipedia.org/wiki/Continuous_uniform_distribution

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