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Added becomes_ta()
to determine the sample size when a unit enter the take-all stratum.
Internal changes to the way classes are instantiated. No user-visible changes.
Updated maintainer email.
Added a vignette.
A single sample size is now recycled for each stratum when drawing samples or calculating inclusion probabilities.
Added a cutoff
argument that puts units with sizes above the cutoff into a take-all stratum.
sps
objects now inherit from numeric instead of integer.
Replacement methods for length
and levels
no longer mangle sps
objects.
prop_allocation()
gets a new argument for breaking ties. The default now breaks ties according to the references; the old behavior can be had by setting ties = "first"
.
Argument names for prop_allocation()
, expected_coverage()
, and sps_repweights()
have changed to be either more descriptive, or consistent with the names for other functions.
Fixed a bug when calculating inclusion probabilities that could result in ties not breaking according to position (as documented) when alpha > 0
.
Simplified the codebase.
Added a new argument alpha
for calculating inclusion probabilities. It can be used to place units with inclusion probabilities close to 1 into the take-all stratum. This was implicitly 0 in previous versions, but the current default is 1e-4.
All functions can now accept size vectors with zeros.
sps()
is now faster, especially for large populations.
Added a function factory to generate other order sampling methods.
This version has a number of non-backwards compatible changes to address undesirable behavior with some functions.
Largest-remainder rounding could result in prop_allocation()
giving visibly non-proportional allocations, so it has been removed. The default is now the Jefferson/D’Hondt method.
The method
argument in prop_allocation()
has been replaced with the divisor
argument to supply a divisor function for rounding.
The initial
argument in prop_allocation()
is recycled to ensure the initial allocation is feasible when supplying a single value. This change is not strictly backwards compatible as values that could not be ordinarily recycled no longer give an error.
Supplying a vector of permanent random numbers to sps()
or ps()
that are generated with a given seed now gives the same result when setting that seed prior to calling sps()
or ps()
. This means that setting the seed to a given value can give a different sample compared to older versions, although permanent random numbers should be used for reproducible samples.
The argument name for specifying strata is now strata
instead of s
in all functions. Partial matching means this change won’t break existing code.
prop_allocation()
gains two new arguments:
initial
sets the initial allocation for each stratum. This saves from having to manually keep track of an initial allocation and adjust the sample size passed to prop_allocation()
.
method
selects the apportionment method used to round a proportional allocation to integer values. In particular, highest-averages methods can be used in place of the largest-remainder method.
The defaults for these arguments do not change the behavior of the function from previous versions.
A few convenience functions have been added:
ps()
for drawing ordinary Poisson samples with the same interface as sps()
.
inclusion_prob()
for generating inclusion probabilities for a frame.
expected_coverage()
for calculating the expected number of strata when sampling from a frame.
Some of the internals have been updated to improve performance with large frames.
Most functions do a little more argument checking. In particular, it is no longer possible to pass length 0 arguments to sps()
, prop_allocation()
, or sps_repweights()
.
Added the option to draw samples with permanent random numbers.
Added methods for Math, Ops, [<-, and [[<- that strip attributes from sps
objects so as not to treat the result as a sample.
sps()
now returns an integer vector (when possible), rather than a double.
printing the matrix of replicate weights now shows row names (if any).
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.