OneWayAnova
Defined in: ds/src/stats/estimators/tests.js:191
Extends
StatisticalTest
Constructors
Constructor
new OneWayAnova(
params?):OneWayAnova
Defined in: ds/src/stats/estimators/tests.js:32
Parameters
params?
Returns
OneWayAnova
Inherited from
StatisticalTest.constructor
Properties
_state
_state:
object
Defined in: ds/src/core/estimators/estimator.js:27
Inherited from
StatisticalTest._state
_warnings
_warnings:
any[]
Defined in: ds/src/core/estimators/estimator.js:29
Inherited from
StatisticalTest._warnings
fitted
fitted:
boolean
Defined in: ds/src/core/estimators/estimator.js:25
Inherited from
StatisticalTest.fitted
params
params:
any
Defined in: ds/src/core/estimators/estimator.js:24
Inherited from
StatisticalTest.params
result
result:
any
Defined in: ds/src/stats/estimators/tests.js:34
Inherited from
StatisticalTest.result
Methods
_prepareArgsForFit()
_prepareArgsForFit(
args?): {columns?:undefined;columnsX:any[];prepared:boolean;raw?:undefined;rows:any[];X:any[][];y:any[]; } | {columns:any[];columnsX?:undefined;prepared:boolean;raw?:undefined;rows:any[];X:any[][];y?:undefined; } | {columns?:undefined;columnsX?:undefined;prepared?:undefined;raw:any[];rows?:undefined;X?:undefined;y?:undefined; }
Defined in: ds/src/core/estimators/estimator.js:367
Convenience helper: parse arguments passed to fit/predict/transform.
Supports declarative table-style inputs:
- fit({ X, y, data, omit_missing })
- fit({ data, columns, … })
Returns an object { X, y, prepared, rows } where X/y are numeric arrays if preparation was required, otherwise returns the original values.
Note: this helper only prepares numeric matrices/vectors using core table utilities; it does not perform encoding of categorical predictors.
Parameters
args?
any[] = []
Returns
{ columns?: undefined; columnsX: any[]; prepared: boolean; raw?: undefined; rows: any[]; X: any[][]; y: any[]; } | { columns: any[]; columnsX?: undefined; prepared: boolean; raw?: undefined; rows: any[]; X: any[][]; y?: undefined; } | { columns?: undefined; columnsX?: undefined; prepared?: undefined; raw: any[]; rows?: undefined; X?: undefined; y?: undefined; }
Inherited from
StatisticalTest._prepareArgsForFit
_repr_html_()
_repr_html_():
string
Defined in: ds/src/core/estimators/estimator.js:201
Observable/Jupyter HTML representation
Returns
string
HTML representation
Inherited from
StatisticalTest._repr_html_
clearWarnings()
clearWarnings():
void
Defined in: ds/src/core/estimators/estimator.js:139
Clear all warnings
Returns
void
Inherited from
StatisticalTest.clearWarnings
fit()
fit(
groups,opts?):OneWayAnova
Defined in: ds/src/stats/estimators/tests.js:192
Fit should be implemented by subclasses.
Return this for chaining.
Parameters
groups
any
opts?
Returns
OneWayAnova
Overrides
StatisticalTest.fit
getMemoryUsage()
getMemoryUsage():
string
Defined in: ds/src/core/estimators/estimator.js:97
Get memory usage in human-readable format
Returns
string
Memory usage string (e.g., “2.3 MB” or “145 KB”)
Inherited from
StatisticalTest.getMemoryUsage
getParams()
getParams():
any
Defined in: ds/src/core/estimators/estimator.js:294
Get a shallow copy of parameters.
Returns
any
Inherited from
StatisticalTest.getParams
getState()
getState():
any
Defined in: ds/src/core/estimators/estimator.js:65
Get comprehensive model state
Returns
any
State information including fitted status, memory estimate, warnings
Inherited from
StatisticalTest.getState
getWarnings()
getWarnings():
any[]
Defined in: ds/src/core/estimators/estimator.js:124
Get all warnings
Returns
any[]
Array of warning objects
Inherited from
StatisticalTest.getWarnings
getWarningsByType()
getWarningsByType(
type):any[]
Defined in: ds/src/core/estimators/estimator.js:148
Get warnings of a specific type
Parameters
type
string
Warning type
Returns
any[]
Filtered warnings
Inherited from
StatisticalTest.getWarningsByType
hasWarnings()
hasWarnings():
boolean
Defined in: ds/src/core/estimators/estimator.js:132
Check if model has warnings
Returns
boolean
Inherited from
StatisticalTest.hasWarnings
isFitted()
isFitted():
boolean
Defined in: ds/src/core/estimators/estimator.js:36
Check if model is fitted
Returns
boolean
Inherited from
StatisticalTest.isFitted
predict()
predict():
void
Defined in: ds/src/core/estimators/estimator.js:424
Predict should be implemented by supervised estimators.
Returns
void
Inherited from
StatisticalTest.predict
save()
save():
string
Defined in: ds/src/core/estimators/estimator.js:329
Save model to JSON string
Returns
string
JSON representation of the model
Inherited from
StatisticalTest.save
setParams()
setParams(
params?):OneWayAnova
Defined in: ds/src/core/estimators/estimator.js:285
Set parameters (mutates instance).
Parameters
params?
any = {}
Returns
OneWayAnova
Inherited from
StatisticalTest.setParams
summary()
summary():
any
Defined in: ds/src/stats/estimators/tests.js:37
Returns
any
Inherited from
StatisticalTest.summary
toJSON()
toJSON():
object
Defined in: ds/src/stats/estimators/tests.js:44
Serialize minimal model metadata. Subclasses may override to include learned parameters.
Returns
object
__class__
__class__:
string
fitted
fitted:
boolean
params
params:
any
result
result:
any
Inherited from
StatisticalTest.toJSON
transform()
transform():
void
Defined in: ds/src/core/estimators/estimator.js:431
Transform should be implemented by transformers.
Returns
void
Inherited from
StatisticalTest.transform
fromJSON()
staticfromJSON(obj?):StatisticalTest
Defined in: ds/src/stats/estimators/tests.js:53
Basic deserialization. Subclasses should override if they need to restore learned arrays / matrices.
Parameters
obj?
Returns
StatisticalTest
Inherited from
StatisticalTest.fromJSON
load()
staticload(jsonString):Estimator
Defined in: ds/src/core/estimators/estimator.js:346
Load model from JSON string
Parameters
jsonString
string
JSON representation
Returns
Estimator
Reconstructed estimator instance
Inherited from
StatisticalTest.load