cslr: Chatterjee Simple Linear Regression
In jack-thomas/uwrfRegression: Automated Regression for UWRF Math 327

Performs simple linear regression (with transformations) using the methodology taught by Dr. Arunendu Chatterjee for Fall 2016.

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cslr(x, y, matrix.out = F, asm.out = F, anova.out = F, shapiro.out = F,
  bp.out = F, summary.out = F, plot.out = T, conf.out = F,
  conf.level = 0.95)

`x`	a vector of x values (representing the independent variable).
`y`	a vector of y values (representing the dependent variable).
`matrix.out`	whether to provide a matrix of adjusted R-squared values
`asm.out`	whether to provide results of assumption checking.
`anova.out`	whether to provide ANOVA results.
`shapiro.out`	whether to provide results of the Shapiro-Wilk test.
`bp.out`	whether to provide results of the Breusch-Pagan test.
`summary.out`	whether to provide summary of best regression.
`plot.out`	whether to provide relevant plots.
`conf.out`	whether to create confidence intervals for coefficients.
`conf.level`	confidence level for conf.out.