0.4.0
This is a long overdue release of pykelihood
with many breaking changes that have accumulated over time.
Breaking changes
- Renamed
stats_utils
module toprofiler
- Data must now be provided to kernels on creation, unbound kernels are
no longer allowed Parameter
s are no longer subclasses offloat
, use.value
to get
their stored valueConditioningMethod
s were removed, their uses can be replaced with
score functions- The
biv
parameter to theProfiler
was removed, confidence
intervals are univariate only
Removed
Many distributions and utilities which were created with a specific use
case in mind and aren't generally useful have been removed:
MixtureExponentialModel
,ExtendedGPD
,PointProcess
,CompositionDistribution
,DetrendedFluctuationAnalysis
,pettitt_test
,threshold_selection_GoF
andthreshold_selection_gpd_NorthorpColeman
,- extreme values visualisation routines,
- process samplers (Poisson and Hawkes).
New features
- Metrics:
{pp,qq}_l{1,2}_distance
,likelihood
,expo_ratio
- Log-normal distribution
- Plotting functions now accept an
ax
argument to use instead of the
globalplt
figure - Constant kernel (most useful for testing)
Kernel
s have awith_covariate
method that returns a new kernel
with the provided data as covariate, but all parameters are kept the
same- The
random_state
parameter to theDistribution.rvs
method is now
explicit and no longer hidden in the**kwargs
Bug fixes
- Fixed
fit_instance
for nested kernels with fixed values - Fixed the
TruncatedDistribution
which forgot its bounds after fitting - A parameter which shows up in several places in a distribution will
keep the same value when fitting instead of returning independent
parameters
Other
- Add section to README on fitting other score functions than the likelihood
- Add changelog with all version changes up to this one