Questions tagged [trimmed-mean]

A k-trimmed mean is a mean where the largest and smallest k% of the observations are removed before the mean is calculated.

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How can I draw a interaction plot using trimmed means?

I am conducting two-way ANOVA in r using the t2way function in WRS2 packages for my thesis. t2way function, as you know, uses trimmed mean to escape from the severe problem of heterogeneity of ...
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How does the 30% trimmed mean of this equal 6.167?

[6, 3, 7, 11, 5, 3, 8, 7, 2, 6, 9, 13, 10, 4, 3] So I'm going through some revision for stats, one of the questions asks to find the trimmed mean of the above data. I've worked it out but my answer ...
1 vote
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Calculating the trimmed mean as an estimator

My book provides the following steps to calculate the $100 \alpha$ percent trimmed mean for a sample data of $n$ measurments: 1-Order the measurments. 2-Discard the smallest $100\alpha$ percent and ...
470 views

If we are taught to not remove outliers without investigation, how do robust methods (median, trimmed mean) can be even suggested?

I just saw an article, which taught to nor remove outliers without investigation, because it may be a unusual but valid observation or naturally skewed data, for example in chemistry or medicine. Only ...
4k views

Use and misuse of Winsorization

I am doing research on Winsorization (and trimming), which has been broadly applied in many fields, but I think many researchers didn't do it in a "rigorous" way. Or maybe even worse, they misuse it. ...
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Given independence, is the median of a product equal to the product of the medians?

Question: Assume $X$ and $Y$ are independent random variables. Is $Median(XY) = Median(X) \cdot Median(Y)$? If so, how would one prove this? If not, what conditions would be sufficient for this ...
614 views

Combining similarity scores

I have a list of m x n similarity score matrix, something like ...
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Mean has lower standard error than 5% trimmed mean?

I'm investigating using a trimmed mean to measure the location of various distributions. The distributions sometimes are heavily contaminated and sometimes not. Usually they follow something similar ...
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Do methods based on trimmed means require homoscedasticity?

I understand (from Wilcox' book [1]) that methods using the trimmed means are robust to distributional assumptions. Do the methods (e.g. bwtrim, from the ...
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1 vote
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Examining the relative efficiency of the trimmed mean

Using the following reference A survey of sampling from contaminated distributions, I am trying to investigate the relative efficiency (RE) for the mean vs the trimmed mean, given the following ...
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For what distribution is a trimmed mean the maximum likelihood estimator?

The sample mean is the maximum likelihood estimator of $\mu$ for a normal distribution $\text{Normal}(\mu,\sigma)$. The sample median is the maximum likelihood estimator of $m$ for a Laplace ...
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How to interpret output from least trimmed squares estimate and compare it to OLS?

I have to compute and compare the least squares method on a model to the least trimmed method. The LS model results were: ...
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Is it allowed to use a 5% trimmed mean for analyzing data from a creativity task (quantity of ideas)?

For my research I conducted a creativity test and measured the quantity of ideas subjects had. Some people are extreme outliers as they have a lot of ideas or only 1 or 2 ideas. Intuitively I wanted ...
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1 vote
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Measure of central tendency for an ex-gaussian distribution

I know there won't be a clear answer to that question but I'm really curious to know your opinion on that matter. I deal with reaction times, and finding a good measure of central tendency is ...
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Is R's trimmed means function biased?

I've been trying to understand how R's trimmed mean function works. I suspect it might be biased, but would like to get feedback here before I file a bug-report (if this is an inappropriate forum for ...
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