View source: R/outlierDetection.R
filterLogLinear | R Documentation |
Removes fish records that fall outside an acceptable weight-length region defined by the log-linear model
weight=alfa\*length^beta\*exp(epsilon); epsilon~N(0,sigma^2)
with alfa=exp(logalfa), logalfa and other parameters corresponding to arguments to this function.
filterLogLinear(
individuals,
logalfa,
beta,
sigma,
kAl,
kAu = kAl,
weightCol = "IndividualRoundWeight",
lengthCol = "IndividualTotalLength"
)
individuals |
|
logalfa |
The alfa parameter (on a log scale) for the log-linear model |
beta |
The beta parameter for the log-linear model |
sigma |
The standard deviation of weight for the log-linear model |
kAl |
Number of standard deviations (on a log scale) that defines the lower limit of the acceptable region |
kAu |
Number of standard deviations (on a log scale) that defines the upper limit of the acceptable region |
weightCol |
name of column in 'individuals' that contain fish weight (in a unit corresponding to alfa and beta). Default correspond to the Individual level of |
lengthCol |
name of column in 'individuals' that contain fish length (in a unit corresponding to alfa and beta). Default correspond to the Individual level of |
This function is intended to provide the same filtering that is offered in ECA 3.x and ECA 4.x for removing outliers based on a log-linear weight-length model, and function arguments are named to correspond to the naming convention used in ECA.
Records are removed if their weights that outside the range from: alfa\*L^beta\*exp(kAu\*sigma) to alfa\*L^beta\*exp(-kAl\*sigma)
any records with missing length or weight is not removed.
Note that kAl and kAu are given on a log scale, so that the acceptable region is not symmetric around the growth curve when kAl=kAu.
data.table
, like individuals, but with some records removed.
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