- N
double N [@property getter]
- kurtosis
double kurtosis [@property getter]
- max
double max [@property getter]
- mean
double mean [@property getter]
- min
double min [@property getter]
- mse
double mse [@property getter]
Mean squared error. In other words, a biased estimate of variance.
- skewness
double skewness [@property getter]
- stdev
double stdev [@property getter]
- sum
double sum [@property getter]
- toMeanSD
MeanSD toMeanSD [@property getter]
Converts this struct to a MeanSD. Called via alias this when an
implicit conversion is attetmpted.
- var
double var [@property getter]
Output range to compute mean, stdev, variance, skewness, kurtosis, min, and * max online. Using this struct is relatively expensive, so if you just need * mean and/or stdev, try MeanSD or Mean. Getter methods for stdev, * var cost a few floating point ops. Getter for mean costs a single branch to * check for N == 0. Getters for skewness and kurtosis cost a whole bunch of * floating point ops. This struct uses O(1) space and does *NOT* store the * individual elements. * * Note: This struct can implicitly convert to a MeanSD. * * References: Computing Higher-Order Moments Online. * http://people.xiph.org/~tterribe/notes/homs.html * * Examples: * --- * Summary summ; * summ.put(1); * summ.put(2); * summ.put(3); * summ.put(4); * summ.put(5); * assert(summ.N == 5); * assert(summ.mean == 3); * assert(summ.stdev == sqrt(2.5)); * assert(summ.var == 2.5); * assert(approxEqual(summ.kurtosis, -1.9120)); * assert(summ.min == 1); * assert(summ.max == 5); * assert(summ.sum == 15); * ---