splitValueCalculate: Calculates a single value that is a function of an...

In growthPheno: Functional Analysis of Phenotypic Growth Data to Smooth and Extract Traits

Calculates a single value that is a function of an individual's values for a response

Description

Splits the values of a response into subsets corresponding individuals and applies a function that calculates a single value from each individual's observations. It includes the ability to calculate the observation number that is closest to the calculated value of the function and the assocated values of a factor or numeric.

Note: this function is soft deprecated and may be removed in future versions.
Use byIndv_ValueCalc.

Usage

splitValueCalculate(response, weights=NULL, individuals = "Snapshot.ID.Tag", 
                    FUN = "max", which.obs = FALSE, which.values = NULL, 
                    data, na.rm=TRUE, sep=".", ...)

Arguments

response	A character giving the name of the column in data from which the values of FUN are to be calculated.
weights	A character giving the name of the column in data containing the weights to be supplied as w to FUN.
individuals	A character giving the name of the factor that defines the subsets of the data for which each subset corresponds to the response values for an individual (e.g. plant, pot, cart, plot or unit).
FUN	A character giving the name of the function that calculates the value for each subset.
which.obs	A logical indicating whether or not to determine the observation number corresponding to the observed value that is closest to the value of the function, in addition to the value of the function itself. That is, FUN need not return an observed value of the reponse, e.g. quantile. In the case of multiple observed response values satisfying this condition, the first is returned.
which.values	A character giving the name of the factor or numeric whose values are associated with the response values and whose value is to be returned for the observation number whose response value corresponds to the observed value closest to the value of the function. That is, FUN need not return an observed value of the reponse, e.g. quantile. In the case of multiple observed response values satisfying this condition, the value of the which.values vector for the first of these is returned.
data	A data.frame containing the column from which the function is to be calculated.
na.rm	A logical indicating whether NA values should be stripped before the calculation proceeds.
sep	A character giving the separator to use when the levels of individuals are combined. This is needed to avoid using a character that occurs in a factor to delimit levels when the levels of individuals are combined to identify subsets.
...	allows for arguments to be passed to FUN.

Value

A data.frame, with the same number of rows as there are individuals, containing a column for the individuals and a column with the values of the function for the individuals. It is also possible to determine observaton numbers or the values of another column in data for the response values that are closest to the FUN results, using either or both of which.obs and which.values. If which.obs is TRUE, a column with observation numbers is included in the data.frame. If which.values is set to the name of a factor or a numeric,a column containing the levels of that factor or the values of that numeric is included in the data.frame.

The name of the column with the values of the function will be formed by concatenating the response and FUN, separated by a full stop. If which.obs is TRUE, the column name for the obervations numbers will have .obs added after FUN into the column name for the function values; if which.values is specified, the column name for these values will have a full stop followed by which.values added after FUN into the column name for the function values.

Author(s)

Chris Brien

See Also

intervalValueCalculate, splitContGRdiff, splitSplines

Examples

data(exampleData)
sPSA.max.dat <- splitValueCalculate("sPSA", data = longi.dat)
AGR.max.dat <- splitValueCalculate("sPSA.AGR", FUN="max", data=longi.dat, 
                                    which.values = "DAP", which.obs = TRUE)
sPSA.dec1.dat <- splitValueCalculate("sPSA", FUN="quantile", data=longi.dat, 
                                     which.values = "DAP", probs = 0.1)

growthPheno documentation built on Oct. 24, 2023, 5:08 p.m.