----+ Choropleth map +---------------------------------------------------------------------------------------------
clmethod(method) specifies the method to be used for classifying variable attribute and representing its spatial
distribution as a choropleth map.
clmethod(quantile) is the default and requests that the quantiles method be used.
clmethod(boxplot) requests that the boxplot method be used.
clmethod(eqint) requests that the equal intervals method be used.
clmethod(stdev) requests that the standard deviates method be used.
clmethod(kmeans) requests that the k-means method be used.
clmethod(custom) requests that class breaks be specified by the user with option clbreaks(numlist).
clmethod(unique) requests that each value of variable attribute be treated as a distinct class.
clnumber(#) specifies the number of classes k in which variable attribute is to be divided.
When the quantiles, equal intervals, standard deviates, or k-means classification method is chosen, the default is clnumber(4). When the boxplot classification method is chosen, this option is inactive and k=6.
When the custom classification method is chosen, this option is inactive and k equals the number of elements of numlist specified in option clbreaks(numlist) minus 1.
When the unique classification method is chosen, this option is inactive and k equals the number of different values taken on by variable attribute.
clbreaks(numlist) is required when option clmethod(custom) is specified. It defines the custom class breaks to be used for classifying variable attribute. numlist should be specified so that the first element is the minimum value of variable attribute to be considered; the second to kth elements are the class breaks; and the last element is the maximum value of variable attribute to be considered. For example, suppose we want to group the values of variable attribute into the following four classes: [10,15], (15,20], (20,25] and (25,50]; for this we must specify clbreaks(10 15 20 25 50).