sample.size.floored.variance

alpha

margin

The variable being sampled as a vector.

dependent.variable

Numeric weights (if present) as a vector.

weights

Returns necessary sample size for a given power and dataset, but treats any standard deviation below 0.1 as 0.1

internal

Contains kernel smoothing tools designed for use by historical
dialectologists and philologists for exploring spatial and temporal patterns
in noisy historical language data, such as that obtained from historical texts.
The main way in which these might differ from other implementations of kernel
smoothing is that they assume that the function (linguistic variable) being
explored has the form of the relative frequency of a series of discrete
possibilities (linguistic variants). This package also offers a way of exploring
distributions in 2-dimensional space and in time with separate kernels, and
tools for identifying appropriate bandwidths for these.

sample.size.floored.variance: Sample size floored variance

Description

Usage

Arguments

Value