LinearModelSummary (baseCode 1.1.11 API)

java.lang.Object
- ubic.basecode.math.linearmodels.LinearModelSummary

All Implemented Interfaces:

Serializable
```
public class LinearModelSummary
extends Object
implements Serializable
```
Represents the results of a linear model analysis from R. Both the summary.lm and anova objects are represented. FIXME make this have the capabilities of the "fit" object, rather than just the summary.

Author:

paul

See Also:

Serialized Form

Field Summary

Fields
Modifier and Type Field and Description

static String INTERCEPT_COEFFICIENT_NAME

Fields
Modifier and Type	Field and Description
`static String`	`INTERCEPT_COEFFICIENT_NAME`

Constructor Summary

Constructors
Modifier	Constructor and Description
`protected`	`LinearModelSummary()` Construct an empty summary.
	`LinearModelSummary(org.rosuda.REngine.REXP summaryLm, org.rosuda.REngine.REXP anova, String[] factorNames)` Construct from the result of evaluation of an R call. should be deprecated because we're not using R integration
	`LinearModelSummary(String key)` Construct an empty summary.
	`LinearModelSummary(String k, Double[] coefficients, Double[] residuals, List<String> terms, DoubleMatrix<String,String> contrastCoefficients, Double[] effects, Double[] stdevUnscaled, double rsquared, double adjRsquared, double fstat, Integer ndof, Integer ddof, GenericAnovaResult anovaResult, double sigma, boolean isShrunken)`

Method Summary

All Methods Instance Methods Concrete Methods
Modifier and Type	Method and Description
`Double`	`getAdjRSquared()`
`GenericAnovaResult`	`getAnova()`
`Double[]`	`getCoefficients()`
`DoubleMatrix<String,String>`	`getContrastCoefficients()`
`Map<String,Double>`	`getContrastCoefficients(String factorName)`
`Map<String,Double>`	`getContrastCoefficientStderr(String factorName)` For the requested factor, return the standard errors associated with the contrast coefficient estimates.
`Map<String,Double>`	`getContrastPValues(String factorName)`
`Map<String,Double>`	`getContrastTStats(String factorName)`
`Double[]`	`getEffects()`
`Double`	`getF()`
`List<String>`	`getFactorNames()`
`List<String>`	`getFactorValueNames(String factorName)` Return the factor names in the order they are stored here.
`String`	`getFormula()`
`Double`	`getInteractionEffectP(String... fnames)`
`Double`	`getInterceptCoeff()`
`Double`	`getInterceptP()`
`Double`	`getInterceptT()`
`String`	`getKey()`
`Collection<String>`	`getMainEffectFactorNames()`
`Double`	`getMainEffectP(String factorName)`
`Integer`	`getNumeratorDof()`
`Double`	`getP()` Overall p value for F stat of model fit (upper tail probability)
`Double`	`getPriorDof()`
`Integer`	`getResidualDof()`
`Double[]`	`getResiduals()`
`Double`	`getRSquared()`
`Double`	`getSigma()` Residual standard deviation
`Double[]`	`getStdevUnscaled()` Unscaled standard deviations for the coefficient estimators in same order as coefficients.
`boolean`	`hasInteractions()`
`boolean`	`isBaseline(String factorValueName)`
`boolean`	`isShrunken()` Whether this is the result of emprical bayes shrinkage of variance estimates
`void`	`setAnova(GenericAnovaResult genericAnovaResult)`
`void`	`setKey(String key)`
`void`	`setPriorDof(Double priorDof)`
`String`	`toString()`

Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait

- Field Detail
  - INTERCEPT_COEFFICIENT_NAME
```
public static final String INTERCEPT_COEFFICIENT_NAME
```
    See Also:
    
    Constant Field Values
- Constructor Detail
  - LinearModelSummary
```
public LinearModelSummary(org.rosuda.REngine.REXP summaryLm,
                          org.rosuda.REngine.REXP anova,
                          String[] factorNames)
```
    Construct from the result of evaluation of an R call. should be deprecated because we're not using R integration
    
    Parameters:
    
    summaryLm -
    
    anova -
    
    factorNames - as referred to in the model. Used as keys to keep track of coefficients etc.
  - LinearModelSummary
```
public LinearModelSummary(String key)
```
    Construct an empty summary. Use for model fits that fail due to 0 degrees of freedom, etc.
    
    Parameters:
    
    key - identifier
  - LinearModelSummary
```
public LinearModelSummary(String k,
                          Double[] coefficients,
                          Double[] residuals,
                          List<String> terms,
                          DoubleMatrix<String,String> contrastCoefficients,
                          Double[] effects,
                          Double[] stdevUnscaled,
                          double rsquared,
                          double adjRsquared,
                          double fstat,
                          Integer ndof,
                          Integer ddof,
                          GenericAnovaResult anovaResult,
                          double sigma,
                          boolean isShrunken)
```
    Parameters:
    
    k - optional identifier
    
    coefficients -
    
    residuals -
    
    terms -
    
    contrastCoefficients -
    
    effects - AKA Qty
    
    rsquared -
    
    adjRsquared -
    
    fstat -
    
    ndof -
    
    ddof -
    
    anovaResult -
    
    sigma -
    
    isShrunken -
  - LinearModelSummary
```
protected LinearModelSummary()
```
    Construct an empty summary. Use for model fits that fail due to 0 residual degrees of freedom, etc.
- Method Detail
  - getAdjRSquared
```
public Double getAdjRSquared()
```
    Returns:
    
    the adjRSquared
  - getAnova
```
public GenericAnovaResult getAnova()
```
    Returns:
    
    may be null if ANOVA was not run.
  - getCoefficients
```
public Double[] getCoefficients()
```
  - getContrastCoefficients
```
public DoubleMatrix<String,String> getContrastCoefficients()
```
    Returns:
    
    The contrast coefficients and associated statistics for all tested contrasts.
    Row names are the contrasts, for example for a model with one factor "f" with two levels "a" and "b": {"(Intercept)", "fb"}. columns are always {"Estimate" ,"Std. Error", "t value", "Pr(>|t|)"}
  - getContrastCoefficients
```
public Map<String,Double> getContrastCoefficients(String factorName)
```
    Parameters:
    
    factorName -
    
    Returns:
  - getContrastCoefficientStderr
```
public Map<String,Double> getContrastCoefficientStderr(String factorName)
```
    For the requested factor, return the standard errors associated with the contrast coefficient estimates.
    
    Parameters:
    
    factorName -
    
    Returns:
  - getContrastPValues
```
public Map<String,Double> getContrastPValues(String factorName)
```
    Parameters:
    
    factorName -
    
    Returns:
    
    Map of pvalues for the given factor. For continuous factors or factors with only one level, there will be just one value. For factors with N>2 levels, there will be N-1 values, one for each contrast (since we compute treatment contrasts to the baseline)
  - getContrastTStats
```
public Map<String,Double> getContrastTStats(String factorName)
```
    Parameters:
    
    factorName -
    
    Returns:
    
    Map of T statistics for the given factor. For continuous factors or factors with only one level, there will be just one value. For factors with N>2 levels, there will be N-1 values, one for each contrast (since we compute treatment contrasts to the baseline)
  - getEffects
```
public Double[] getEffects()
```
    Returns:
  - getF
```
public Double getF()
```
    Returns:
    
    F statistic for overall model fit.
  - getFactorNames
```
public List<String> getFactorNames()
```
    Returns:
    
    the factorNames
  - getFactorValueNames
```
public List<String> getFactorValueNames(String factorName)
```
    Return the factor names in the order they are stored here. Pvalues and T statistics for this factor are in the same order, but the 'baseline' must be accounted for.
    
    Parameters:
    
    factorName -
    
    Returns:
  - getFormula
```
public String getFormula()
```
    Returns:
    
    the formula
  - getInteractionEffectP
```
public Double getInteractionEffectP(String... fnames)
```
    Parameters:
    
    fnames - names of the factors
    
    Returns:
    
    See Also:
    
    ubic.basecode.math.linearmodels.GenericAnovaResult#getInteractionEffectP(java.lang.String)
  - getInterceptCoeff
```
public Double getInterceptCoeff()
```
    Returns:
  - getInterceptP
```
public Double getInterceptP()
```
    Returns:
  - getInterceptT
```
public Double getInterceptT()
```
    Returns:
  - getKey
```
public String getKey()
```
  - getMainEffectFactorNames
```
public Collection<String> getMainEffectFactorNames()
```
    Returns:
    
    See Also:
    
    GenericAnovaResult.getMainEffectFactorNames()
  - getMainEffectP
```
public Double getMainEffectP(String factorName)
```
    Parameters:
    
    factorName -
    
    Returns:
    
    overall p-value for the given factor
    
    See Also:
    
    GenericAnovaResult.getMainEffectP(java.lang.String)
  - getNumeratorDof
```
public Integer getNumeratorDof()
```
    Returns:
  - getP
```
public Double getP()
```
    Overall p value for F stat of model fit (upper tail probability)
    
    Returns:
    
    value or NaN if it can't be computed for some reason
  - getPriorDof
```
public Double getPriorDof()
```
    Returns:
    
    the priorDof
  - getResidualDof
```
public Integer getResidualDof()
```
    Returns:
  - getResiduals
```
public Double[] getResiduals()
```
    Returns:
    
    the residuals
  - getRSquared
```
public Double getRSquared()
```
    Returns:
    
    the rSquared
  - getSigma
```
public Double getSigma()
```
    Residual standard deviation
    
    Returns:
  - getStdevUnscaled
```
public Double[] getStdevUnscaled()
```
    Unscaled standard deviations for the coefficient estimators in same order as coefficients. The standard errors are given by stdev.unscaled * sigma (a la limma)
  - hasInteractions
```
public boolean hasInteractions()
```
    Returns:
    
    See Also:
    
    GenericAnovaResult.hasInteractions()
  - isBaseline
```
public boolean isBaseline(String factorValueName)
```
  - isShrunken
```
public boolean isShrunken()
```
    Whether this is the result of emprical bayes shrinkage of variance estimates
    
    Returns:
  - setAnova
```
public void setAnova(GenericAnovaResult genericAnovaResult)
```
    Parameters:
    
    genericAnovaResult -
  - setKey
```
public void setKey(String key)
```
  - setPriorDof
```
public void setPriorDof(Double priorDof)
```
    Parameters:
    
    priorDof - the priorDof to set
  - toString
```
public String toString()
```
    Overrides:
    
    toString in class Object

Class LinearModelSummary

Field Summary

Constructor Summary

Method Summary

Methods inherited from class java.lang.Object

Field Detail

INTERCEPT_COEFFICIENT_NAME

Constructor Detail

LinearModelSummary

LinearModelSummary

LinearModelSummary

LinearModelSummary

Method Detail

getAdjRSquared

getAnova

getCoefficients

getContrastCoefficients

getContrastCoefficients

getContrastCoefficientStderr

getContrastPValues

getContrastTStats

getEffects

getF

getFactorNames

getFactorValueNames

getFormula

getInteractionEffectP

getInterceptCoeff

getInterceptP

getInterceptT

getKey

getMainEffectFactorNames

getMainEffectP

getNumeratorDof

getP

getPriorDof

getResidualDof

getResiduals

getRSquared

getSigma

getStdevUnscaled

hasInteractions

isBaseline

isShrunken

setAnova

setKey

setPriorDof

toString