Calculate the distribution of costs for the installation of an elevator based on the different distribution rules.

Provides functions for constructing and evaluating
    CUSUM charts and RA-CUSUM charts with focus on false signal probability.

Create CUSUM (cumulative sum) statistics from a vector or dataframe.
    Also create single or faceted CUSUM control charts, with or without control limits.
    Accepts vector, dataframe, tibble or data.table inputs.

Computation of decision intervals (H) and average run lengths (ARL) for CUSUM charts. Details of the method are seen in Hawkins and Olwell (2012): Cumulative sum charts and charting for quality improvement, Springer Science & Business Media.

Seek the significant cutoff value for a continuous variable, which will 
    be transformed into a classification, for linear regression, 
    logistic regression, logrank analysis and cox regression. First of all, 
    all combinations will be gotten by combn() function. Then n.per argument, 
    abbreviated of total number percentage, will be used to remove the combination 
    of smaller data group. In logistic, Cox regression and logrank analysis, 
    we will also use p.per argument, patient percentage, to filter the lower 
    proportion of patients in each group. Finally, p value in regression 
    results will be used to get the significant combinations and output 
    relevant parameters. In this package, there is no limit to the number of 
    cutoff points, which can be 1, 2, 3 or more. Still, we provide 2 methods, 
    typical Bonferroni and Duglas G (1994) <doi: 10.1093/jnci/86.11.829>, to 
    adjust the p value, Missing values will be deleted by na.omit() function 
    before analysis.

Estimate cutpoints that optimize a specified metric in binary classification tasks
    and validate performance using bootstrapping. Some methods for more robust cutpoint
    estimation are supported, e.g. a parametric method assuming normal distributions,
    bootstrapped cutpoints, and smoothing of the metric values per cutpoint using
    Generalized Additive Models. Various plotting functions are included. For an overview
    of the package see Thiele and Hirschfeld (2021) <doi:10.18637/jss.v098.i11>.