What Can OnlineStats Do?

Statistic/Model	OnlineStat
Univariate Statistics:
mean	`Mean`
variance	`Variance`
quantiles via SGD	`QuantileSGD`
quantiles via Online MM	`QuantileMM`
max and min	`Extrema`
skewness and kurtosis	`Moments`
sum	`Sum`
difference	`Diff`
Multivariate Analysis:
covariance matrix	`CovMatrix`
k-means clustering	`KMeans`
multiple univariate statistics	`MV{<:OnlineStat}`
Density Estimation:
Beta	`FitBeta`
Categorical	`FitCategorical`
Cauchy	`FitCauchy`
Gamma	`FitGamma`
LogNormal	`FitLogNormal`
Normal	`FitNormal`
Multinomial	`FitMultinomial`
MvNormal	`FitMvNormal`
Statistical Learning:
GLMs with regularization	`StatLearn`
Linear (also ridge) regression	`LinReg`
Other:
Bootstrapping	`Bootstrap`
approximate count of distinct elements	`HyperLogLog`
Reservoir Sampling	`ReservoirSample`