public class ModelMetricsHGLMV3<I extends ModelMetricsHGLM,S extends ModelMetricsHGLMV3<I,S>> extends ModelMetricsBaseV3<I,S>
SchemaV3.Meta
Schema.AutoParseable
Modifier and Type | Field and Description |
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long |
bad |
double |
caic |
boolean |
converge |
double |
convergence |
double |
dfrefe |
double[] |
fixef |
double |
hlik |
double |
pbvh |
double |
pvh |
int[] |
randc |
double[] |
ranef |
double[] |
sefe |
double[] |
sere |
double |
sumetadiffsquare |
double[] |
summvc1 |
double[][] |
summvc2 |
double |
varfix |
double[] |
varranef |
custom_metric_name, custom_metric_value, description, frame, frame_checksum, model, model_category, model_checksum, MSE, nobs, predictions, RMSE, scoring_time
Constructor and Description |
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ModelMetricsHGLMV3() |
Modifier and Type | Method and Description |
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S |
fillFromImpl(ModelMetricsHGLM modelMetrics)
Fill this Schema from the given implementation object.
|
fillFromImpl
createAndFillImpl, createImpl, extractVersionFromSchemaName, fillFromAny, fillFromBody, fillFromImpl, fillFromImpl, fillFromParms, fillFromParms, fillFromParms, fillImpl, fillImpl, getImplClass, getImplClass, getSchemaName, getSchemaType, getSchemaVersion, init_meta, markdown, markdown, newInstance, newInstance, setField, setSchemaType_doNotCall
asBytes, clone, copyOver, frozenType, read, readExternal, readJSON, reloadFromBytes, toJsonBytes, toJsonString, write, writeExternal
@API(help="dispersion parameter of the mean model (residual variance for LMM)", direction=OUTPUT) public double varfix
@API(help="dispersion parameter of the random effects (variance of random effects for GLMM", direction=OUTPUT) public double[] varranef
@API(help="deviance degrees of freedom for mean part of the model", direction=OUTPUT) public double dfrefe
@API(help="estimates, standard errors of the linear predictor in the dispersion model", direction=OUTPUT) public double[] summvc1
@API(help="estimates, standard errors of the linear predictor for dispersion parameter of random effects", direction=OUTPUT) public double[][] summvc2
@API(help="adjusted profile log-likelihood profiled over random effects", direction=OUTPUT) public double pvh
@API(help="adjusted profile log-likelihood profiled over fixed and random effects", direction=OUTPUT) public double pbvh
@API(help="sum(etai-eta0)^2 where etai is current eta and eta0 is the previous one", direction=OUTPUT) public double sumetadiffsquare
public S fillFromImpl(ModelMetricsHGLM modelMetrics)
Schema
fillFromImpl
in class Schema<I extends ModelMetricsHGLM,S extends ModelMetricsHGLMV3<I,S>>