Uses of Class
microsim.data.MultiKeyCoefficientMap

Packages that use MultiKeyCoefficientMap

Package	Description
microsim.data
microsim.data.db
microsim.data.excel
microsim.statistics.regression

Uses of MultiKeyCoefficientMap in microsim.data

Methods in microsim.data that return MultiKeyCoefficientMap

Modifier and Type	Method	Description
MultiKeyCoefficientMap	MultiKeyCoefficientMap.clone()	Returns a deep clone copy of the MultiKeyCoefficientMap object
static MultiKeyCoefficientMap	MultiKeyCoefficientMapFactory.createMapFromAnnotatedList(List<?> list)

Uses of MultiKeyCoefficientMap in microsim.data.db

Methods in microsim.data.db that return MultiKeyCoefficientMap

Modifier and Type	Method	Description
static MultiKeyCoefficientMap	DatabaseUtils.loadCoefficientMap(jakarta.persistence.EntityManager entityManager, Class<?> clazz)
static MultiKeyCoefficientMap	DatabaseUtils.loadCoefficientMap(Class<?> clazz)

Uses of MultiKeyCoefficientMap in microsim.data.excel

Methods in microsim.data.excel that return MultiKeyCoefficientMap

Modifier and Type	Method	Description
static MultiKeyCoefficientMap	ExcelAssistant.loadCoefficientMap(String excelFileName, String sheetName, int keyColumns)	Load MultiKeyCoefficientMap from Excel spreadsheet data, reading from the first line of the spreadsheet, and automatically finds the last line of the spreadsheet (blank lines within the data are not allowed and will result in a NullPointerException).
static MultiKeyCoefficientMap	ExcelAssistant.loadCoefficientMap(String excelFileName, String sheetName, int keyColumns, int valueColumns)	Load MultiKeyCoefficientMap from Excel spreadsheet data, reading from the first line of the spreadsheet, and automatically finds the last line of the spreadsheet (blank lines within the data are not allowed and will result in a NullPointerException).
static MultiKeyCoefficientMap	ExcelAssistant.loadCoefficientMap(String excelFileName, String sheetName, int keyColumns, int valueColumns, int startLine, int endLine)	Load MultiKeyCoefficientMap from Excel spreadsheet data, choosing which line to start reading from via the startLine parameter

Uses of MultiKeyCoefficientMap in microsim.statistics.regression

Methods in microsim.statistics.regression that return MultiKeyCoefficientMap

Modifier and Type	Method	Description
static MultiKeyCoefficientMap	RegressionUtils.appendCoefficientMaps(MultiKeyCoefficientMap primaryMap, MultiKeyCoefficientMap secondaryMap)	Appends @secondaryMap to @primaryMap
static MultiKeyCoefficientMap	RegressionUtils.appendCoefficientMaps(MultiKeyCoefficientMap primaryMap, MultiKeyCoefficientMap secondaryMap, String secondaryKeyPrefix)
static MultiKeyCoefficientMap	RegressionUtils.appendCoefficientMaps(MultiKeyCoefficientMap primaryMap, MultiKeyCoefficientMap secondaryMap, String secondaryKeyPrefix, boolean invertSecondary)
static MultiKeyCoefficientMap	RegressionUtils.bootstrap(MultiKeyCoefficientMap map)	Method to bootstrap regression covariates.
static MultiKeyCoefficientMap	RegressionUtils.bootstrap(MultiKeyCoefficientMap coefficients, MultiKeyCoefficientMap covarianceMatrix)	Method to bootstrap regression covariates.

Methods in microsim.statistics.regression that return types with arguments of type MultiKeyCoefficientMap

Modifier and Type	Method	Description
static <T> Map<T,MultiKeyCoefficientMap>	RegressionUtils.bootstrapMultinomialRegression(Map<T,MultiKeyCoefficientMap> eventRegressionCoefficientMap, MultiKeyCoefficientMap covarianceMatrix, Class<T> enumType)	Method to bootstrap multinomial regression covariates.
static <E extends Enum<E> & IntegerValuedEnum> Map<E,MultiKeyCoefficientMap>	RegressionUtils.populateMultinomialCoefficientMap(Class<E> clazz, MultiKeyCoefficientMap multinomialCoefficients)	Method to package multinomialCoeffMap

Methods in microsim.statistics.regression with parameters of type MultiKeyCoefficientMap

Modifier and Type	Method	Description
static MultiKeyCoefficientMap	RegressionUtils.appendCoefficientMaps(MultiKeyCoefficientMap primaryMap, MultiKeyCoefficientMap secondaryMap)	Appends @secondaryMap to @primaryMap
static MultiKeyCoefficientMap	RegressionUtils.appendCoefficientMaps(MultiKeyCoefficientMap primaryMap, MultiKeyCoefficientMap secondaryMap, String secondaryKeyPrefix)
static MultiKeyCoefficientMap	RegressionUtils.appendCoefficientMaps(MultiKeyCoefficientMap primaryMap, MultiKeyCoefficientMap secondaryMap, String secondaryKeyPrefix, boolean invertSecondary)
static MultiKeyCoefficientMap	RegressionUtils.bootstrap(MultiKeyCoefficientMap map)	Method to bootstrap regression covariates.
static MultiKeyCoefficientMap	RegressionUtils.bootstrap(MultiKeyCoefficientMap coefficients, MultiKeyCoefficientMap covarianceMatrix)	Method to bootstrap regression covariates.
static <T> Map<T,MultiKeyCoefficientMap>	RegressionUtils.bootstrapMultinomialRegression(Map<T,MultiKeyCoefficientMap> eventRegressionCoefficientMap, MultiKeyCoefficientMap covarianceMatrix, Class<T> enumType)	Method to bootstrap multinomial regression covariates.
static double	LinearRegression.computeScore(MultiKeyCoefficientMap coeffMultiMap, Object agent)	To be used when the agent Object has member fields that correspond by name to all the regressors of the Regression's MultiKeyCoefficientMap map.
static double	LinearRegression.computeScore(MultiKeyCoefficientMap amap, Map<String,Double> values)	Warning - only use when LinearRegression object contains a MultiKeyCoefficientMap with only one key.
static <T extends Enum<T>> double	LinearRegression.computeScore(MultiKeyCoefficientMap coeffMultiMap, IDoubleSource iDblSrc, Class<T> enumType)	Uses reflection to obtain information from the iDblSrc object, so it is possibly slow.
static <T extends Enum<T>> double	LinearRegression.computeScore(MultiKeyCoefficientMap coeffMultiMap, IDoubleSource iDblSrc, Class<T> enumType, boolean singleKeyCoefficients)	Use this method when the underlying agent does not have any additional conditioning regression keys (such as the gender or civil status) to determine the appropriate regression co-efficients, i.e. the regression co-efficients do not depend on any properties of the underlying model.
static <T extends Enum<T>, U extends Enum<U>> double	LinearRegression.computeScore(MultiKeyCoefficientMap coeffMultiMap, IDoubleSource iDblSrc, Class<T> enumTypeDouble, IObjectSource iObjSrc, Class<U> enumTypeObject)	Requires the implementation of the IObjectSource to ascertain whether any additional conditioning regression keys are used (e.g. whether the underlying agent is female, married etc., where the regression co-efficients are conditioned on additional keys of gender and civil status, for example).
<E extends Enum<E>> double	ProbabilityCalculator.getProbability(MultiKeyCoefficientMap map, IDoubleSource iDblSrc, Class<E> Regressors)
<E extends Enum<E>> double	ProbabilityCalculator.getProbability(MultiKeyCoefficientMap map, IDoubleSource iDblSrc, Class<E> Regressors, double adjust)
<E extends Enum<E>> double	ProbabilityCalculator.getScore(MultiKeyCoefficientMap map, IDoubleSource iDblSrc, Class<E> Regressors)
static <E extends Enum<E> & IntegerValuedEnum> Map<E,MultiKeyCoefficientMap>	RegressionUtils.populateMultinomialCoefficientMap(Class<E> clazz, MultiKeyCoefficientMap multinomialCoefficients)	Method to package multinomialCoeffMap

Method parameters in microsim.statistics.regression with type arguments of type MultiKeyCoefficientMap

Modifier and Type	Method	Description
static <T> Map<T,MultiKeyCoefficientMap>	RegressionUtils.bootstrapMultinomialRegression(Map<T,MultiKeyCoefficientMap> eventRegressionCoefficientMap, MultiKeyCoefficientMap covarianceMatrix, Class<T> enumType)	Method to bootstrap multinomial regression covariates.

Constructors in microsim.statistics.regression with parameters of type MultiKeyCoefficientMap

Modifier	Constructor	Description
	BinomialRegression(RegressionType type, Class<E1> enumType, MultiKeyCoefficientMap map)
	GeneralisedOrderedRegression(RegressionType type, Class<E1> enumType, MultiKeyCoefficientMap multinomialCoefficients)
	LinearRegression(MultiKeyCoefficientMap map)	Construct a linear regression object.
	MultinomialRegression(RegressionType type, Class<E1> enumType, MultiKeyCoefficientMap multinomialCoefficients)
	OrderedRegression(RegressionType type, Class<E1> enumType, MultiKeyCoefficientMap map)

Constructor parameters in microsim.statistics.regression with type arguments of type MultiKeyCoefficientMap

Modifier	Constructor	Description
	MultinomialRegression(RegressionType type, Class<E1> enumType, Map<E1,MultiKeyCoefficientMap> maps, boolean preProcessedFlag)