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Typedef

Static Public Summary
public

KComplexInputData: Complex | number | boolean | string | Array<number> | {_re: number, _im: number} | {doubleValue: number} | {toString: function}

Complex type argument.
public

Matrix type argument.
public

Collection of calculation settings for matrix.
public

Analysis of variance.
public

Output for multiple regression analysis
public

Regression table.
public

Regression table data.
public

Settings for multiple regression analysis
public

Vector state
public
public

Output for principal component analysis.
public

Settings for principal component analysis.
public

Collection of calculation settings for matrix.
public

Collection of calculation settings for matrix.

Static Public

public KComplexInputData: Complex | number | boolean | string | Array<number> | {_re: number, _im: number} | {doubleValue: number} | {toString: function} source

Complex type argument.

  • Complex
  • number
  • boolean
  • string
  • Array<number>
  • {_re:number,_im:number}
  • {doubleValue:number}
  • {toString:function}

Initialization can be performed as follows.

  • 1200, "1200", "12e2", "1.2e3"
  • "3 + 4i", "4j + 3", [3, 4].

public KMatrixInputData: Complex source

Matrix type argument.

  • Matrix
  • Complex
  • number
  • string
  • Array<string|number|Complex|Matrix>
  • Array<Array<string|number|Complex|Matrix>>
  • {doubleValue:number}
  • {toString:function}

Initialization can be performed as follows.

  • 10, "10", "3 + 4j", "[ 1 ]", "[1, 2, 3]", "[1 2 3]", [1, 2, 3],
  • [[1, 2], [3, 4]], "[1 2; 3 4]", "[1+2i 3+4i]",
  • "[1:10]", "[1:2:3]" (MATLAB / Octave / Scilab compatible).

public KMatrixSettings: Object source

Collection of calculation settings for matrix.

  • Available options vary depending on the method.

Properties:

NameTypeAttributeDescription
dimension string | ?number
  • optional
  • default: "auto"
  • nullable: true

Calculation direction. 0/"auto", 1/"row", 2/"column", 3/"both".
correction Object
  • optional

Correction value. For statistics. 0(unbiased), 1(sample).

public KMultipleRegressionAnalysisAnova: Object source

Analysis of variance. ANOVA.

Properties:

NameTypeAttributeDescription
regression KMultipleRegressionAnalysisVectorState

regression.
residual KMultipleRegressionAnalysisVectorState

residual error.
total KMultipleRegressionAnalysisVectorState

total.
F number

F value. Dispersion ratio (F0)
significance_F number

Significance F. Test with F distribution with q, n-q-1 degrees of freedom.(Probability of error.)

public KMultipleRegressionAnalysisOutput: Object source

Output for multiple regression analysis

Properties:

NameTypeAttributeDescription
q number

number of explanatory variables.
n number

number of samples.
predicted_values number[][]

predicted values. (column vector)
sY number

Variance of predicted values of target variable.
sy number

Variance of measured values of target variable.
multiple_R number

Multiple R. Multiple correlation coefficient.
R_square number

R Square. Coefficient of determination.
adjusted_R_square number

Adjusted R Square. Adjusted coefficient of determination.
ANOVA KMultipleRegressionAnalysisAnova

analysis of variance.
Ve number

Unbiased variance of residuals. (Ve)
standard_error number

Standard error. (SE)
AIC number

Akaike's Information Criterion. (AIC)
regression_table KMultipleRegressionAnalysisPartialRegression

Regression table.

public KMultipleRegressionAnalysisPartialRegression: Object source

Regression table.

Properties:

NameTypeAttributeDescription
intercept KMultipleRegressionAnalysisPartialRegressionData

Intercept.
parameters KMultipleRegressionAnalysisPartialRegressionData[]

Parameters.

public KMultipleRegressionAnalysisPartialRegressionData: Object source

Regression table data.

Properties:

NameTypeAttributeDescription
coefficient number

Coefficient.
standard_error number

Standard error.
t_stat number

t-statistic.
p_value number

P-value. Risk factor.
lower_95 number

Lower limit of a 95% confidence interval.
upper_95 number

Upper limit of a 95% confidence interval.

public KMultipleRegressionAnalysisSettings: Object source

Settings for multiple regression analysis

Properties:

NameTypeAttributeDescription
samples KMatrixInputData

explanatory variable. (Each column is a parameters and each row is a samples.)
target KMatrixInputData

response variable. / actual values. (column vector)
is_standardised boolean
  • optional
  • default: false

Use standardized partial regression coefficients.

public KMultipleRegressionAnalysisVectorState: Object source

Vector state

Properties:

NameTypeAttributeDescription
df number

degree of freedom
SS number

sum of squares
MS number

unbiased_variance

public KPrincipalComponent: Object source

Properties:

NameTypeAttributeDescription
eigen_value number

Contribution. Eigen value. Variance of principal components.
factor_loading number[]

Factor loading. Eigen vector. Principal component coefficients.
factor_loading_contribution_rate number[]

Factor loading contribution rate.
cumulative_contribution_ratio number

Cumulative contribution ratio.
contribution_ratio number

Contribution ratio.
score number[]

Principal component score.

public KPrincipalComponentAnalysisOutput: Object source

Output for principal component analysis.

Properties:

NameTypeAttributeDescription
principal_component KPrincipalComponent[]

Principal component.

public KPrincipalComponentAnalysisSettings: Object source

Settings for principal component analysis.

Properties:

NameTypeAttributeDescription
samples KMatrixInputData

explanatory variable. (Each column is a parameters and each row is a samples.)
is_unbiased boolean
  • optional
  • default: true

Use unbiased variance when calculating variance from samples.
is_standardised boolean
  • optional
  • default: false

Use standardized explanatory variables. Use the correlation matrix instead of the covariance matrix.

public KSignalSettings: Object source

Collection of calculation settings for matrix.

  • Available options vary depending on the method.

Properties:

NameTypeAttributeDescription
dimension string | ?number
  • optional
  • default: "auto"
  • nullable: true

Calculation direction. 0/"auto", 1/"row", 2/"column", 3/"both".

public KStatisticsSettings: Object source

Collection of calculation settings for matrix.

  • Available options vary depending on the method.

Properties:

NameTypeAttributeDescription
dimension string | ?number
  • optional
  • default: "auto"
  • nullable: true

Calculation direction. 0/"auto", 1/"row", 2/"column", 3/"both".
correction Object
  • optional

Correction value. For statistics. 0(unbiased), 1(sample).