Package index • mcr

All functions
`MCResult-class` `calcBias,MCResult-method` `calcCUSUM,MCResult-method` `calcResponse,MCResult-method` `getCoefficients,MCResult-method` `getData,MCResult-method` `getErrorRatio,MCResult-method` `getRegmethod,MCResult-method` `getResiduals,MCResult-method` `getFitted,MCResult-method` `getWeights,MCResult-method` `plot,MCResult-method` `plotBias,MCResult-method` `plotDifference,MCResult-method` `plotResiduals,MCResult-method` `printSummary,MCResult-method` `coef,MCResult-method` `summary,MCResult-method`	Class `"MCResult"`
`MCResult.calcBias()`	Systematical Bias Between Reference Method and Test Method
`MCResult.calcCUSUM()`	Calculate CUSUM Statistics According to Passing & Bablok (1983)
`MCResult.calcResponse()`	Calculate Response with Confidence Interval.
`MCResult.getCoefficients()`	Get Regression Coefficients
`MCResult.getData()`	Get Data
`MCResult.getErrorRatio()`	Get Error Ratio
`MCResult.getFitted()`	Get Fitted Values.
`MCResult.getRegmethod()`	Get Regression Method
`MCResult.getResiduals()`	Get Regression Residuals
`MCResult.getWeights()`	Get Weights of Data Points
`MCResult.initialize()`	MCResult Object Initialization
`MCResult.plot()`	Scatter Plot Method X vs. Method Y
`MCResult.plotBias()`	Plot Estimated Systematical Bias with Confidence Bounds
`MCResult.plotDifference()`	Bland-Altman Plot
`MCResult.plotResiduals()`	Plot Residuals of an MCResult Object
`MCResult.printSummary()`	Print Summary of a Regression Analysis
`MCResultAnalytical-class` `calcResponse,MCResultAnalytical-method` `printSummary,MCResultAnalytical-method` `summary,MCResultAnalytical-method`	Class `"MCResultAnalytical"`
`MCResultAnalytical.calcResponse()`	Caluculate Response
`MCResultAnalytical.initialize()`	Initialize Method for 'MCResultAnalytical' Objects.
`MCResultAnalytical.printSummary()`	Print Regression-Analysis Summary for Objects of class 'MCResultAnalytical'.
`MCResultBCa-class` `calcResponse,MCResultBCa-method` `printSummary,MCResultBCa-method` `summary,MCResultBCa-method`	Class `"MCResultBCa"`
`MCResultBCa.bootstrapSummary()`	Compute Bootstrap-Summary for 'MCResultBCa' Objects.
`MCResultBCa.calcResponse()`	Caluculate Response
`MCResultBCa.initialize()`	Initialize Method for 'MCResultBCa' Objects.
`MCResultBCa.plotBootstrapCoefficients()`	Plot distriblution of bootstrap coefficients
`MCResultBCa.plotBootstrapT()`	Plot distriblution of bootstrap pivot T
`MCResultBCa.printSummary()`	Print Regression-Analysis Summary for Objects of class 'MCResultBCa'.
`MCResultJackknife-class` `calcResponse,MCResultJackknife-method` `getRJIF,MCResultJackknife-method` `plotwithRJIF,MCResultJackknife-method` `printSummary,MCResultJackknife-method` `summary,MCResultJackknife-method`	Class `"MCResultJackknife"`
`MCResultJackknife.calcResponse()`	Caluculate Response
`MCResultJackknife.getJackknifeIntercept()`	Get-Method for Jackknife-Intercept Value.
`MCResultJackknife.getJackknifeSlope()`	Get-Method for Jackknife-Slope Value.
`MCResultJackknife.getJackknifeStatistics()`	Jackknife Statistics
`MCResultJackknife.getRJIF()`	Relative Jackknife Influence Function
`MCResultJackknife.initialize()`	Initialize Method for 'MCResultJackknife' Objects.
`MCResultJackknife.plotwithRJIF()`	Plotting the Relative Jackknife Influence Function
`MCResultJackknife.printSummary()`	Print Regression-Analysis Summary for Objects of class 'MCResultJackknife'.
`MCResultResampling-class` `calcResponse,MCResultResampling-method` `printSummary,MCResultResampling-method` `summary,MCResultResampling-method`	Class `"MCResultResampling"`
`MCResultResampling.bootstrapSummary()`	Compute Bootstrap-Summary for 'MCResultResampling' Objects.
`MCResultResampling.calcResponse()`	Caluculate Response
`MCResultResampling.initialize()`	Initialize Method for 'MCResultAnalytical' Objects.
`MCResultResampling.plotBootstrapCoefficients()`	Plot distriblution of bootstrap coefficients
`MCResultResampling.plotBootstrapT()`	Plot distriblution of bootstrap pivot T
`MCResultResampling.printSummary()`	Print Regression-Analysis Summary for Objects of class 'MCResultResampling'.
`calcDiff()`	Calculate difference between two numeric vectors that gives exactly zero for very small relative differences.
`compareFit()`	Graphical Comparison of Regression Parameters and Associated Confidence Intervals
`creatinine`	Comparison of blood and serum creatinine measurement
`includeLegend()`	Include Legend
`mc.PBequi()`	Equivariant Passing-Bablok Regression
`mc.analytical.ci()`	Analytical Confidence Interval
`mc.bootstrap()`	Resampling estimation of regression parameters and standard errors.
`mc.calc.Student()`	Student Method for Calculation of Resampling Confidence Intervals
`mc.calc.bca()`	Bias Corrected and Accelerated Resampling Confidence Interval
`mc.calc.quant()`	Quantile Calculation for BCa
`mc.calc.quantile()`	Quantile Method for Calculation of Resampling Confidence Intervals
`mc.calc.tboot()`	Bootstrap-t Method for Calculation of Resampling Confidence Intervals
`mc.calcAngleMat.R()`	Calculate Matrix of All Pair-wise Slope Angles
`mc.calcAngleMat()`	Calculate Matrix of All Pair-wise Slope Angles
`mc.calcLinnetCI()`	Jackknife Confidence Interval
`mc.calcTstar()`	Compute Resampling T-statistic.
`mc.deming()`	Calculate Unweighted Deming Regression and Estimate Standard Errors
`mc.linreg()`	Calculate ordinary linear Regression and Estimate Standard Errors
`mc.make.CIframe()`	Returns Results of Calculations in Matrix Form
`mc.paba.LargeData()`	Passing-Bablok Regression for Large Datasets
`mc.paba()`	Passing-Bablok Regression
`mc.wdemingConstCV()`	Calculate Weighted Deming Regression
`mc.wlinreg()`	Calculate Weighted Ordinary Linear Regression and Estimate Standard Errors
`mcr` `mcr-package`	Method Comparison Regression
`mcreg()`	Comparison of Two Measurement Methods Using Regression Analysis
`newMCResult()`	MCResult Object Constructor with Matrix in Wide Format as Input
`newMCResultAnalytical()`	MCResultAnalytical object constructor with matrix in wide format as input.
`newMCResultBCa()`	MCResultBCa object constructor with matrix in wide format as input.
`newMCResultJackknife()`	MCResultJackknife Object Constructor with Matrix in Wide Format as Input
`newMCResultResampling()`	MCResultResampling object constructor with matrix in wide format as input.

Reference

All functions