A collection of functions to construct A-optimal block designs for comparing test treatments with one or more control(s). Mainly A-optimal balanced treatment incomplete block designs, weighted A-optimal balanced treatment incomplete block designs, A-optimal group divisible treatment designs and A-optimal balanced bipartite block designs can be constructed using the package. The designs are constructed using algorithms based on linear integer programming. To the best of our knowledge, these facilities to construct A-optimal block designs for comparing test treatments with one or more controls are not available in the existing R packages. For more details on designs for tests versus control(s) comparisons, please see Hedayat, A. S. and Majumdar, D. (1984) <doi:10.1080/00401706.1984.10487989> A-Optimal Incomplete Block Designs for Control-Test Treatment Comparisons, Technometrics, 26, 363-370 and Mandal, B. N. , Gupta, V. K., Parsad, Rajender. (2017) <doi:10.1080/03610926.2015.1071394> Balanced treatment incomplete block designs through integer programming. Communications in Statistics - Theory and Methods 46(8), 3728-3737.

It can sometimes be difficult to ascertain when some events (such as property crime)
    occur because the victim is not present when the crime happens. As a result, police databases often
    record a 'start' (or 'from') date and time, and an 'end' (or 'to') date and time. The time span between
    these date/times can be minutes, hours, or sometimes days, hence the term 'Aoristic'. 
    Aoristic is one of the past tenses in Greek and represents an uncertain occurrence in time. 
    For events with a location describes with either a latitude/longitude, or X,Y coordinate pair, 
    and a start and end date/time, this package generates an aoristic data frame with aoristic weighted
    probability values for each hour of the week, for each observation. The coordinates are not 
    necessary for the program to calculate aoristic weights; however, they are part of this package 
    because a spatial component has been integral to aoristic analysis from the start. Dummy 
    coordinates can be introduced if the user only has temporal data. Outputs include an aoristic 
    data frame, as well as summary graphs and displays.   
        For more information see:
    Ratcliffe, JH (2002) Aoristic signatures and the temporal analysis of high volume crime patterns, 
    Journal of Quantitative Criminology. 18 (1): 23-43.
    Note: This package replaces an original 'aoristic' package (version 0.6) by George Kikuchi that 
    has been discontinued with his permission.