GlobalVars: CAMP RST Global Variables

In tmcd82070/CAMP_RST: CAMP RST R Routines

CAMP RST Global Variables

Description

Function to run at the beginning to define global variables.

Usage

GlobalVars(
  db.file = "..\\Data\\CAMP.mdb",
  output.dir = "..\\outputs",
  sql.code.dir = file.path(find.package("campR"), "sql"),
  samplePeriodCutTime = "04:00:00",
  max.ok.gap = 2,
  fishingGapMinutes = 10080,
  knotMesh = 15,
  halfConeMulti = 2,
  sample.size.forkLength = 100,
  sample.size.forkLengthAndWeight = 100,
  weight.prop.forkLength = 0.5,
  forkLength.mean.diff = 10,
  time.zone = "America/Los_Angeles",
  Yes.code = 1,
  No.code = 2,
  seed = 884,
  forkLengthCutPoints = data.frame(lifeStage = c("FL1 leq 41mm", "FL2 42-72mm",
    "FL3 73-110mm", "FL4 geq 111mm"), cutPoints = c(41, 72, 110, 9999)),
  passageRounder = 4,
  eff.min.spline.samp.size = 10,
  unassd.sig.digit = 1,
  bootstrap.CI.fx = "f.ci",
  R = 100
)

Arguments

db.file	Character string giving the full path and name of the CAMP Access data base file. Path relative to getwd() can be used.
output.dir	Directory for all output.
sql.code.dir	Directory containing all the SQL code required by campR. Defaults to the sql directory of the installed campR package. By default, all SQL code should be placed in the inst/sql directory in the campR code repository.
samplePeriodCutTime	String giving the sample period cut off for batch date assignment, in military time. Default value is "04:00:00". This is used to assign batch dates that are missing. If a sample period ends before this time on a particular day, the batch date assigned is the previous day. If a sample period ends after this time, batch date assigned is the day that the sampling period ends (i.e., current day). For example, assuming samplePeriodCutTime="04:00:00", a sample period ending at 01:00:00 (1 am) would assign catch to the previous day. A sample period ending at 07:00:00 (7 am) would assign catch to the current day. See routine F.assign.batch.date.
max.ok.gap	Maximum gap, in hours, that is "okay." Default value is 2. Temporal gaps in trapping smaller than this are subsumed by the most immediate preceding valid trapping instance. Gaps in trapping bigger than this get assigned an imputed catch from the GAM model. Because the GAM model for imputation predicts an hourly rate, this max gap cannot be < 1 hour.
fishingGapMinutes	Maximum gap, in minutes, that is NOT okay. Default value is 10,080 minutes or 7 days. Gaps in fishing greater than this constitute a "big" gap, and no imputation is performed. The GAM models are unstable for "big" gaps. In these cases, the season is broken into two periods (before and after the gap) and treated as two separate traps.
knotMesh	The number of data points required per smoothing spline knot. Default value is 15. For example, knotMesh=15 means each additional knot in a smoothing spline requires an additional 15 data points. A linear fit requires at least 15 data points, a quadratic requires at least 30 data points, etc. This restriction helps assure smoothing splines have adequate support and are stable.
halfConeMulti	The multiplication factor to use for expanding fish caught during half-cone operations. Default value is 2. For example, if 15 fish were caught during half cone operation, the analysis considers this halfConeMulti*15 fish.
sample.size.forkLength	Number of fish with measured fork length required to assign life stage. Default value is 100.
sample.size.forkLengthAndWeight	Number of fish with measured fork length and weight required to use weight in the assignment of life stage. Default value is 100.
weight.prop.forkLength	The minimum proportion of fish with weight to fish with fork length in order to use weight in assignment of life stage. Default value is 0.5.
forkLength.mean.diff	When the number of life stage groups (2 or 3) is not specified, the clustering algorithm starts with 3 groups and reduces groups if the mean difference in forklength between groups is less than this number. Units are same as fork lengths (mm). Default value is 10 mm.
time.zone	Time zone to assign to all times. Default value is "America/Los_Angeles", or Pacific time. It would likely never happen, but these routines cannot correctly account for times in two different zones. For example, one trap in one time zone, and another trap in a second zone. This might only happen if a future analysis combined sites over large areas (e.g., states). In the current routines, all times are assigned (or forced) to be in this time zone.
Yes.code	Integer defining the code for "Yes". Usually 2. This code is given in an Access look-up table named table.names["yes.no.codes"]. Unless it has changed, this table was named "luNoYes" in Access. To read this code from Access, an ODBC connection is established and disconnected during execution of this routine.
No.code	Integer defining the code for "No". Usually 1. This code is given in an Access look-up table named table.names["yes.no.codes"]. Unless it has changed, this table was named "luNoYes" in Access. To read this code from Access, an ODBC connection is established and disconnected during execution of this routine.
seed	An integer specifying the seed to use in all functions utilizing a random draw. Currently set equal to 884.
forkLengthCutPoints	A dataframe specifying the groups into which fish are to be partitioned via forklength. The first column containing text strings, which must be named lifeStage, contains new group names, while the second column containing integers, which must be named cutPoints, specifies the right end point of the interval of the forklength range corresponding to the group name represented by that row in dataframe forkLengthCutPoints. Intervals are assumed closed on the right. The number of rows in forkLengthCutPoints should equal the number of desired groups. Finally, the last row should have a right-end point equal or in excess to the maximum possible forklength, e.g., 999. See Details.
passageRounder	An integer specifying the place to which final passage estimates and confidence intervals should be rounded. For example, a value of 4 rounds results to the nearest 1,000.
eff.min.spline.samp.size	An integer specifying the number of efficiency trials required to fit a spline efficiency model. If fewer than this number of efficiency trials target a particular subsite, the Platform estimates constant efficiency for that subsite using the ROM method (see F.efficiency.model). If this number or more are available, the Platform fits increasingly complex spline-based logistic regressions and uses the one with lowest AIC.
unassd.sig.digit	A positive integer specifiying the number of significant digits to which unassigned fish should be estimated during the plus-count algorithm. Values other than zero allow for fractional representation of less common fish types (e.g., Winter or Smolt) during passage estimation. For example, when unassd.sig.digit=1, plus-count fish are rounded to the nearest tenth. Setting unassd.sig.digit=0 rounds to the nearest whole fish.
bootstrap.CI.fx	The function, entered as a character string, to use for identifying (1 - α)\% bootstrapped confidence bounds for passage. Current options include "f.bias.acc.ci" or "f.ci". Default is "f.ci".
R	The number of replicates to use for the bootstrap. Default is 100.

Details

One additional global variable is defined. table.names is a list containing the mapping of table names in Access to table names in R. This was set up to facilitate painless table name changes in Access. This should not change unless tables or table names in Access change. Because these rarely change, we purposefully left this variable out of the arguments to GlobalVars. To change table names, edit the code of GlobalVars and recompile the package.

In dataframe forkLengthCutPoints, cut point intervals are closed on the right. For example, if the second column of forkLengthCutPoints contains the integers 37, 59, and 105, then it is assumed that three forklength intervals are desired. The first will cover (0,37], the second (37,59], and the third (59,105]. The code assumes maximum forklength to be included is the maximum number given (i.e., 105 in the example). Cut points must be set so that the last (and greatest) number is larger than the maximum forklength to include. It is acceptable to set the last cut point to a large number, e.g., Inf or 999, to ensure all forklengths are included in the new grouping scheme.

The Access data base name in use is written to the R log file.

Global variable unassd.sig.digit allows for more robust estimation of fish captured with lesser frequencies, e.g., endangered fish for which estimation of passage is deemed useful. Often, underlying non-randomly-sampled fish are caught in insufficient quantities to allow for the estimation of at least one of these special fish types, when rounded to the nearest fish following the application of underlying frequency distributions resulting from randomly sampled fish. Manipulation of the decimal place following the allocation of these unassigned fish leads to non-zero estimates for rare categories represented in the random sample.

Value

No return value.

Author(s)

WEST Inc.

Examples

## Not run: 
#   ---- Change data base file.
GlobalVars(db.file="../../Platform/data/StanislawCAMP.mdb" ) 

#   ---- Change where output goes.
GlobalVars(ouput.dir="~/Camp_output" ) 


## End(Not run)

tmcd82070/CAMP_RST documentation built on April 6, 2022, 12:07 a.m.