Provides an efficient method to recover the missing block of an approximately low-rank matrix. Current literature on matrix completion focuses primarily on independent sampling models under which the individual observed entries are sampled independently. Motivated by applications in genomic data integration, we propose a new framework of structured matrix completion (SMC) to treat structured missingness by design [Cai T, Cai TT, Zhang A (2016) <doi:10.1080/01621459.2015.1021005>]. Specifically, our proposed method aims at efficient matrix recovery when a subset of the rows and columns of an approximately low-rank matrix are observed. The main function in our package, smc.FUN(), is for recovery of the missing block A22 of an approximately low-rank matrix A given the other blocks A11, A12, A21.

An open source platform for validation and process control.
    Tools to analyze data from internal validation of forensic short tandem
    repeat (STR) kits are provided. The tools are developed to provide
    the necessary data to conform with guidelines for internal validation
    issued by the European Network of Forensic Science Institutes (ENFSI)
    DNA Working Group, and the Scientific Working Group on DNA Analysis Methods
    (SWGDAM). A front-end graphical user interface is provided.
    More information about each function can be found in the
    respective help documentation.

Construct subtests from a pool of items by using ant-colony-optimization, genetic algorithms, brute force, or random sampling.
  Schultze (2017) <doi:10.17169/refubium-622>.

Download, navigate and analyse the Student-Life dataset. 
    The Student-Life dataset contains passive and automatic sensing data 
    from the phones of a class of 48 Dartmouth college students. 
    It was collected over a 10 week term. Additionally, the dataset contains ecological 
    momentary assessment results along with pre-study and post-study mental  
    health surveys. The intended use is to assess 
    mental health, academic performance and behavioral trends. 
    The raw dataset and additional information is 
    available at <https://studentlife.cs.dartmouth.edu/>.