Authors
James Elsner
Summary
Quantile regression extends ordinary least-squares regression to quantiles of the response variable. Ordinary regression is a model for the conditional mean, where the mean is conditional on the value of the explanatory variable. Likewise, quantile regression is a model for the conditional quantiles. For trend analysis the explanatory variable is time. Quantiles are points taken at regular intervals from the cumulative distribution function of a random variable. The quantiles mark a set of ordered data into equal-sized data subsets. The software is downloaded from the internet and installed on a computer. A data set from the internet is imported into a software session. An exploratory plot of the data is created to visualize the trends. A quantile regression model is fit to the data to quantify the trends and determine their statistical significance.Further details
The protocol was published on Protocol Exchange in 2008. To see the entire protocol, click on the source link.Advertisement
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