* Optimal Thresholding Fisher’s P-Value Combination Method* (

**TFisher**)

We provide the cumulative distribution function (CDF), quantile, and statistical power calculator for a collection of thresholding Fisher’s p-value combination methods, including Fisher’s p-value combination method, truncated product method and, in particular, soft-thresholding Fisher’s p-value combination method which is proven to be optimal in some context of signal detection. The p-value calculator for the omnibus version of these tests are also included. For reference, please see Hong Zhang and Zheyang Wu. ‘Optimal Thresholding of Fisher’s P-value Combination Tests for Signal Detection’, submitted.

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**Large Data Sets****ldat**)

Tools for working with vectors and data sets that are too large to keep in memory. Extends the basic functionality provided in the ‘lvec’ package. Provides basis statistical functionality of ‘lvec’ objects, such as arithmetic operations and calculating means and sums. Also implements ‘data.frame’-like objects storing its data in ‘lvec’ objects.

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**Random Wishart Matrix Generation****rWishart**)

An expansion of R’s ‘stats’ random wishart matrix generation. This package allows the user to generate singular, Uhlig and Harald (1994) <doi:10.1214/aos/1176325375>, and pseudo wishart, Diaz-Garcia, et al.(1997) <doi:10.1006/jmva.1997.1689>, matrices. In addition the user can generate wishart matrices with fractional degrees of freedom, Adhikari (2008) <doi:10.1061/(ASCE)0733-9399(2008)134:12(1029)>, commonly used in volatility modeling. Users can also use this package to create random covariance matrices.

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**Simple Matrix Construction****Massign**)

Constructing matrices for quick prototyping can be a nuisance, requiring the user to think about how to fill the matrix with values using the matrix() function. The %<-% operator solves that issue by allowing the user to construct matrices using code that shows the actual matrices.

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**Multivariate Empirical Density Function****MEPDF**)

Based on the input data an n-dimensional cube with sub cells of user specified side length is created. The number of sample points which fall in each sub cube is counted, and with the cell volume and overall sample size an empirical probability can be computed. A number of cubes of higher resolution can be superimposed. The basic method stems from J.L. Bentley in ‘Multidimensional Divide and Conquer’. J. L. Bentley (1980) <doi:10.1145/358841.358850>.

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**Renewal Hawkes Process****RHawkes**)

Simulate a renewal Hawkes (RHawkes) self-exciting process, with a given immigrant hazard rate function and offspring density function. Calculate the likelihood of a RHawkes process with given hazard rate function and offspring density function for an (increasing) sequence of event times. Calculate the Rosenblatt residuals of the event times. Predict future event times based on observed event times up to a given time. For details see Chen and Stindl (2017) <doi:10.1080/10618600.2017.1341324>.