Changes from ver 1.0-3 to ver 1.1  (2023-04-14)

1) np.boot
	* Added "na.rm = TRUE" when calling the quantile() function
	* Note that NA and NaN can arise using "stud" confidence intervals

2) np.cor.test, np.loc.test, np.reg.test
	* Added "na.rm" argument to handle removal of missing data
	* Default is TRUE which removes missing cases from input data

3) start-up message is now provided
	* prints ascii package name art (if interactive) and version number
	* also provides information about how to cite the package

4) parallel package is no longer required
	* parallel was previously required and automatically attached
	* now parallel package will only be loaded if requested

5) version numbering format change
	* previous versions was 3 digits (1.0-0)
	* new versioning is 2 digits (1.1)



Changes from ver 1.0-2 to ver 1.0-3  (2021-03-01)

1) np.reg.test
	* Added argument "lambda" for ridge regression estimators
	* Improved (stabilized) inverse calculations in internals

2) psdinv (new function)
	* Inverse of positive semi-definite matrix
	* Internal function used by np.reg.test



Changes from ver 1.0-1 to ver 1.0-2  (2020-10-01)

1) np.boot (new function for nonparametric bootstrapping)
	* Provides bootstrap estimates of standard error and bias
	* Computes five different bootstrap confidence intervals

2) Update to package name (to reflect bootstrap extensions)
	* Previous name: Nonparametric Tests via Permutations
	* Updated name: Nonparametric Bootstrap and Permutation Tests



Changes from ver 1.0-0 to ver 1.0-1  (2020-09-10)

1) Added S3 plotting method for all nptest functions
	* Plots the permutation distribution and observed statistic
	* The rejection region is a separate color (default is red)
	* User input "alpha" controls rejection region (default is 0.05)

2) Added new reference to package and np.reg.test()
	* Only relevant for tests of regression coefficients
	* See Helwig (2019b) for details on regression tests
	* https://doi.org//10.1016/j.neuroimage.2019.116030

3) Update to the statistic df in np.cor.test for semi/partial correlations
	* Applicable when z is provided and independent = TRUE
	* Previously used a denominator that ignored the dimension of z
	* The correction does *not* affect the inferential results
          (because the correction is applied to statistic and perm.dist)

4) Update to the statistic df in np.reg.test with nuisance variables
	* Applicable when z is provided, homosced = TRUE, and method %in% c("HJ", "KC", "SW")
	* Previously used a denominator that ignored the dimension of z
	* The correction does *not* affect the inferential results
          (because the correction is applied to statistic and perm.dist)

5) Correction to example in the help file for np.cor.test
	* Previously used data generation code that only worked for rho = 0.5
	* Updated data generation code works for all values of rho

6) Update to package name (to clarify meaning of "Nonparametric Tests")
	* Previous name: Nonparametric Tests
	* Update name: Nonparametric Tests via Permutations