Gives convenient access to publicly available police-recorded open
    crime data from large cities in the United States that are included in the
    Crime Open Database <https://osf.io/zyaqn/>.

A comprehensive collection of datasets exclusively focused on crimes, criminal activities, and related topics. 
    This package serves as a valuable resource for researchers, analysts, and students interested in crime analysis, 
    criminology, social and economic studies related to criminal behavior. Datasets span global and local contexts, 
    with a mix of tabular and spatial data.

A collection of functions that make it easier to understand crime (or other)
    data, and assist others in understanding it. The package helps you read data 
    from various sources, clean it, fix column names, and graph the data.

Implements convex regression with interpretable sharp partitions
    (CRISP), which considers the problem of predicting an outcome variable on the basis of two covariates, using an interpretable yet non-additive model. CRISP partitions the covariate space into blocks in a data-adaptive way, and fits a mean model within each block. Unlike other partitioning methods, CRISP is fit using a non-greedy approach by solving a convex optimization problem, resulting in low-variance fits. More details are provided in Petersen, A., Simon, N., and Witten, D. (2016). Convex Regression with Interpretable Sharp Partitions. Journal of Machine Learning Research, 17(94): 1-31 <http://jmlr.org/papers/volume17/15-344/15-344.pdf>.

Designs guide sequences for CRISPR/Cas9 genome editing and 
    provides information on sequence features pertinent to guide 
    efficiency. Sequence features include annotated off-target 
    predictions in a user-selected genome and a predicted efficiency 
    score based on the model described in Doench et al. (2016) 
    <doi:10.1038/nbt.3437>. Users are able to import additional genomes 
    and genome annotation files to use when searching and annotating 
    off-target hits. All guide sequences and off-target data can be 
    generated through the 'R' console with sgRNA_Design() or through 
    'crispRdesignR's' user interface with crispRdesignRUI(). CRISPR 
    (Clustered Regularly Interspaced Short Palindromic Repeats) and the 
    associated protein Cas9 refer to a technique used in genome editing.