summarize_cluster_discrete: Summarize cluster sample for discrete attributes

In SilviaTerra/forestsamplr: Standard Forest Sampling Design Workups

Description

Summarizes population-level statistics for cluster sample for attribute data. The calculations are derived from Chapter 3 in Avery and Burkhart's (1967) Forest Measurements, Fifth Edition. The variance terms refer to the variance of the mean.

Usage

summarize_cluster_discrete(data, attribute, plotTot = NA,
  desiredConfidence = 0.95)

Arguments

data	data frame containing observations of variable of interest. Attribute (variable of interest) must be the proportion alive in the associated plot.
attribute	character name of attribute to be summarized.
plotTot	numeric population size. Equivalent to the total number of possible plots in the population.
desiredConfidence	numeric desired confidence level (e.g. 0.9).

Value

data frame of stand-level statistics. Includes standard error and confidence interval.

Author(s)

Karin Wolken

Examples

## Not run: 
data <- data.frame(plots = c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10), 
                   propAlive = c(0.75, 0.80, 0.80, 0.85, 0.70,
                   0.90, 0.70, 0.75, 0.80, 0.65))
attribute = 'propAlive'
plotTot = 250
desiredConfidence = 0.95

## End(Not run)

SilviaTerra/forestsamplr documentation built on Jan. 3, 2020, 2:33 p.m.