summarize_cluster: Summarize cluster sample

In SilviaTerra/forestsamplr: Standard Forest Sampling Design Workups

Description

Summarizes population-level statistics for cluster sample 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(data, element = TRUE, attribute = NA,
  desiredConfidence = 0.95)

Arguments

data	data frame containing observations of variable of interest for either cluster-level or element-level data.
element	logical true if parameter data is element-level (plot-level), false if parameter data is cluster-level. Default is True.
attribute	character name of attribute to be summarized.
desiredConfidence	numeric desired confidence level (e.g. 0.9).

Value

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

Author(s)

Karin Wolken

Examples

## Not run: 
dataPlot <- data.frame(clusterID = c(1, 1, 1, 1, 1, 2, 2, 3, 4, 4, 4, 4, 4, 4, 5, 5, 5, 5, 5),
                       attr = c(1000, 1250, 950, 900, 1005, 1000, 1250, 950, 900, 1005, 1000,
                                1250, 950, 900, 1005, 1000, 1250, 950, 900),
                       isUsed = c(T, T, T, T, T, T, T, T, T, T, T, T, T, T, F, F, F, F, F))
element = TRUE
attribute = 'attr'

## End(Not run)

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