docs: fix typos and copy-paste errors in stats TypeScript declarations

lib/node_modules/@stdlib/stats/array/stdev/docs/types/index.d.ts

@@ -35,7 +35,7 @@ type InputArray = NumericArray | Collection<number> | AccessorArrayLike<number>;
 * -   Setting the correction parameter to a value other than `0` has the effect of adjusting the divisor during the calculation of the standard deviation according to `N-c` where `c` corresponds to the provided degrees of freedom adjustment. When computing the standard deviation of a population, setting the correction parameter to `0` is the standard choice (i.e., the provided array contains data constituting an entire population). When computing the corrected sample standard deviation, setting the correction parameter to `1` is the standard choice (i.e., the provided array contains data sampled from a larger population; this is commonly referred to as Bessel's correction).
 *
 * @param x - input array
-* @param correction - degrees of freedom adjustment
+* @param correction - degrees of freedom adjustment (default: 1.0)
 * @returns standard deviation
 *
 * @example

lib/node_modules/@stdlib/stats/base/dists/arcsine/logcdf/docs/types/index.d.ts

@@ -108,7 +108,7 @@ interface LogCDF {
 *
 * var mylogcdf = logcdf.factory( 0.0, 10.0 );
 * y = mylogcdf( 0.5 );
-* // returns ~-1.938
+* // returns ~-1.941
 *
 * y = mylogcdf( 8.0 );
 * // returns ~-0.35

lib/node_modules/@stdlib/stats/base/dists/arcsine/quantile/docs/types/index.d.ts

@@ -25,7 +25,7 @@
 *
 * -   If `p < 0` or `p > 1`, the function returns `NaN`.
 *
-* @param p - input value
+* @param x - input value
 * @returns evaluated quantile function
 */
 type Unary = ( x: number ) => number;
@@ -82,7 +82,7 @@ interface Quantile {
 	( p: number, a: number, b: number ): number;
 
 	/**
-	* Returns a function for evaluating the quantile function for an arcsine distribution with minimum support `a` an maximum support `b`.
+	* Returns a function for evaluating the quantile function for an arcsine distribution with minimum support `a` and maximum support `b`.
 	*
 	* @param a - minimum support
 	* @param b - maximum support
@@ -102,7 +102,7 @@ interface Quantile {
 /**
 * Arcsine distribution quantile function.
 *
-* @param x - input value
+* @param p - input value
 * @param a - minimum support
 * @param b - maximum support
 * @returns evaluated quantile function

lib/node_modules/@stdlib/stats/base/dists/bernoulli/ctor/docs/types/index.d.ts

@@ -93,7 +93,7 @@ declare class Bernoulli {
 	*
 	* @param t - input value
 	* @returns evaluated MGF
-	 */
+	*/
 	mgf( t: number ): number;
 
 	/**

lib/node_modules/@stdlib/stats/base/dists/beta/ctor/docs/types/index.d.ts

@@ -137,7 +137,7 @@ declare class Beta {
 	*
 	* @param t - input value
 	* @returns evaluated MGF
-	 */
+	*/
 	mgf( t: number ): number;
 
 	/**

lib/node_modules/@stdlib/stats/base/dists/binomial/ctor/docs/types/index.d.ts

@@ -122,7 +122,7 @@ declare class Binomial {
 	/**
 	* Evaluates the moment-generating function (MGF).
 	*
-	* @param x - input value
+	* @param t - input value
 	* @returns evaluated MGF
 	*/
 	mgf( t: number ): number;

lib/node_modules/@stdlib/stats/base/dists/binomial/quantile/docs/types/index.d.ts

@@ -45,7 +45,7 @@ interface Quantile {
 	*
 	* @param r - input value
 	* @param n - number of trials
-	* @param p  - success probability
+	* @param p - success probability
 	* @returns evaluated quantile function
 	*
 	* @example
@@ -119,7 +119,7 @@ interface Quantile {
 /**
 * Binomial distribution quantile function.
 *
-* @param p - input value
+* @param r - input value
 * @param n - number of trials
 * @param p - success probability
 * @returns evaluated quantile function

lib/node_modules/@stdlib/stats/base/dists/chi/entropy/docs/types/index.d.ts

@@ -23,7 +23,7 @@
 *
 * ## Notes
 *
-* -   If provided `k < 0`, the function returns `NaN`.
+* -   If provided `k <= 0`, the function returns `NaN`.
 *
 * @param k - degrees of freedom
 * @returns entropy

lib/node_modules/@stdlib/stats/base/dists/chisquare/mgf/docs/types/index.d.ts

@@ -92,7 +92,7 @@ interface MGF {
 *
 * var mymgf = mgf.factory( 1.0 );
 *
-* var y = mymgf( 0.2 );
+* y = mymgf( 0.2 );
 * // returns ~1.291
 *
 * y = mymgf( 0.4 );

lib/node_modules/@stdlib/stats/base/dists/cosine/logpdf/docs/types/index.d.ts

@@ -19,7 +19,7 @@
 // TypeScript Version: 4.1
 
 /**
-* Evaluates the logarithm of the probability density function (PDF) for a raised cosine distribution.
+* Evaluates the natural logarithm of the probability density function (PDF) for a raised cosine distribution.
 *
 * @param x - input value
 * @returns evaluated logPDF
@@ -31,7 +31,7 @@ type Unary = ( x: number ) => number;
 */
 interface LogPDF {
 	/**
-	* Evaluates the logarithm of the probability density function (PDF) for a raised cosine distribution with location parameter `mu` and scale parameter `s` at a value `x`.
+	* Evaluates the natural logarithm of the probability density function (PDF) for a raised cosine distribution with location parameter `mu` and scale parameter `s` at a value `x`.
 	*
 	* ## Notes
 	*
@@ -78,7 +78,7 @@ interface LogPDF {
 	( x: number, mu: number, s: number ): number;
 
 	/**
-	* Returns a function for evaluating the logarithm of the probability density function (PDF) for a raised cosine distribution.
+	* Returns a function for evaluating the natural logarithm of the probability density function (PDF) for a raised cosine distribution.
 	*
 	* @param mu - location parameter
 	* @param s - scale parameter
@@ -96,7 +96,7 @@ interface LogPDF {
 }
 
 /**
-* Raised cosine distribution logarithm of probability density function (PDF).
+* Raised cosine distribution natural logarithm of probability density function (PDF).
 *
 * @param x - input value
 * @param mu - location parameter

lib/node_modules/@stdlib/stats/base/dists/degenerate/ctor/docs/types/index.d.ts

@@ -117,7 +117,7 @@ declare class Degenerate {
 	*
 	* @param t - input value
 	* @returns evaluated MGF
-	 */
+	*/
 	mgf( t: number ): number;
 
 	/**

lib/node_modules/@stdlib/stats/base/dists/degenerate/logcdf/docs/types/index.d.ts

@@ -62,8 +62,8 @@ interface LogCDF {
 	/**
 	* Returns a function for evaluating the natural logarithm of the cumulative distribution function (logCDF) of a degenerate distribution centered at a provided mean value.
 	*
-	* @param mu - value at which to center the distribution
-	* @returns logCDF
+	* @param mu - constant value of distribution
+	* @returns function to evaluate the natural logarithm of the cumulative distribution function
 	*
 	* @example
 	* var mylogcdf = logcdf.factory( 5.0 );

lib/node_modules/@stdlib/stats/base/dists/degenerate/logpmf/docs/types/index.d.ts

@@ -22,7 +22,7 @@
 * Evaluates the natural logarithm of the probability mass function (PMF) for a degenerate distribution.
 *
 * @param x - input value
-* @returns evaluated PMF
+* @returns evaluated logPMF
 */
 type Unary = ( x: number ) => number;
 
@@ -86,7 +86,7 @@ interface LogPMF {
 *
 * var mylogpmf = logpmf.factory( 10.0 );
 *
-* var y = mylogpmf( 10.0 );
+* y = mylogpmf( 10.0 );
 * // returns 0.0
 */
 declare var logpmf: LogPMF;

lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/ctor/docs/types/index.d.ts

@@ -131,7 +131,7 @@ declare class DiscreteUniform {
 	/**
 	* Evaluates the moment-generating function (MGF).
 	*
-	* @param x - input value
+	* @param t - input value
 	* @returns evaluated MGF
 	*/
 	mgf( t: number ): number;

lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/quantile/docs/types/index.d.ts

@@ -87,7 +87,7 @@ interface Quantile {
 	( p: number, a: number, b: number ): number;
 
 	/**
-	* Returns a function for evaluating the quantile function for a discrete uniform distribution with minimum support `a` an maximum support `b`.
+	* Returns a function for evaluating the quantile function for a discrete uniform distribution with minimum support `a` and maximum support `b`.
 	*
 	* @param a - minimum support
 	* @param b - maximum support

lib/node_modules/@stdlib/stats/base/dists/erlang/ctor/docs/types/index.d.ts

@@ -129,7 +129,7 @@ declare class Erlang {
 	*
 	* @param t - input value
 	* @returns evaluated MGF
-	 */
+	*/
 	mgf( t: number ): number;
 
 	/**

lib/node_modules/@stdlib/stats/base/dists/exponential/ctor/docs/types/index.d.ts

@@ -114,7 +114,7 @@ declare class Exponential {
 	*
 	* @param t - input value
 	* @returns evaluated MGF
-	 */
+	*/
 	mgf( t: number ): number;
 
 	/**

lib/node_modules/@stdlib/stats/base/dists/exponential/logpdf/docs/types/index.d.ts

@@ -69,7 +69,7 @@ interface LogPDF {
 	( x: number, lambda: number ): number;
 
 	/**
-	* Returns a function for evaluating the natural logarithm of the probability density function (PDF) for an exponential distribution with parameter `lambda`.
+	* Returns a function for evaluating the natural logarithm of the probability density function (PDF) for an exponential distribution with rate parameter `lambda`.
 	*
 	* @param lambda - rate parameter
 	* @returns logarithm of probability density function (logPDF)

lib/node_modules/@stdlib/stats/base/dists/frechet/ctor/docs/types/index.d.ts

@@ -25,7 +25,7 @@ declare class Frechet {
 	/**
 	* Fréchet distribution constructor.
 	*
-	* @param alpha - shape parameter (default: 0.0)
+	* @param alpha - shape parameter (default: 1.0)
 	* @param s - scale parameter (default: 1.0)
 	* @param m - location parameter (default: 0.0)
 	* @throws `alpha` must be a positive number
@@ -49,12 +49,12 @@ declare class Frechet {
 	* @returns distribution instance
 	*
 	* @example
-	* var Frechet = new Frechet();
+	* var frechet = new Frechet();
 	*
-	* var y = Frechet.cdf( 0.8 );
+	* var y = frechet.cdf( 0.8 );
 	* // returns ~0.287
 	*
-	* var mu = Frechet.mean;
+	* var mu = frechet.mean;
 	* // returns Infinity
 	*/
 	constructor();

lib/node_modules/@stdlib/stats/base/dists/frechet/variance/docs/types/index.d.ts

@@ -20,6 +20,7 @@
 
 /**
 * Returns the variance for a Fréchet distribution with shape `alpha`, scale `s`, and location `m`.
+*
 * ## Notes
 *
 * -   If provided `0 < alpha <= 2` and `s > 0`, the function returns positive infinity.

lib/node_modules/@stdlib/stats/base/dists/gamma/ctor/docs/types/index.d.ts

@@ -132,7 +132,7 @@ declare class Gamma {
 	*
 	* @param t - input value
 	* @returns evaluated MGF
-	 */
+	*/
 	mgf( t: number ): number;
 
 	/**

lib/node_modules/@stdlib/stats/base/dists/gamma/quantile/docs/types/index.d.ts

@@ -76,12 +76,12 @@ interface Quantile {
 	* // returns NaN
 	*
 	* @example
-	* // Non-positive shape parameter:
+	* // Negative shape parameter:
 	* var y = quantile( 0.5, -1.0, 1.0 );
 	* // returns NaN
 	*
 	* @example
-	* // Non-positive rate parameter:
+	* // Negative rate parameter:
 	* var y = quantile( 0.5, 1.0, -1.0 );
 	* // returns NaN
 	*/

lib/node_modules/@stdlib/stats/base/dists/geometric/logpmf/docs/types/index.d.ts

@@ -22,7 +22,7 @@
 * Evaluates the natural logarithm of the probability mass function (PMF) for a geometric distribution.
 *
 * @param x - input value
-* @returns evaluated PMF
+* @returns evaluated logPMF
 */
 type Unary = ( x: number ) => number;
 

lib/node_modules/@stdlib/stats/base/dists/gumbel/ctor/docs/types/index.d.ts

@@ -58,7 +58,7 @@ declare class Gumbel {
 	constructor();
 
 	/**
-	*  Location parameter.
+	* Location parameter.
 	*/
 	mu: number;
 

lib/node_modules/@stdlib/stats/base/dists/halfnormal/entropy/docs/types/index.d.ts

@@ -19,7 +19,7 @@
 // TypeScript Version: 4.1
 
 /**
-* Returns the differential entropy of a half-normal distribution.
+* Returns the differential entropy for a half-normal distribution with scale parameter `sigma`.
 *
 * ## Notes
 *

lib/node_modules/@stdlib/stats/base/dists/invgamma/cdf/docs/types/index.d.ts

@@ -108,7 +108,7 @@ interface CDF {
 *
 * @param x - input value
 * @param alpha - shape parameter
-* @param beta - rate parameter
+* @param beta - scale parameter
 * @returns evaluated CDF
 *
 * @example

lib/node_modules/@stdlib/stats/base/dists/invgamma/logpdf/docs/types/index.d.ts

@@ -102,7 +102,7 @@ interface LogPDF {
 *
 * @param x - input value
 * @param alpha - shape parameter
-* @param beta - rate parameter
+* @param beta - scale parameter
 * @returns evaluated logPDF
 *
 * @example

lib/node_modules/@stdlib/stats/base/dists/invgamma/pdf/docs/types/index.d.ts

@@ -79,7 +79,7 @@ interface PDF {
 	( x: number, alpha: number, beta: number ): number;
 
 	/**
-	* Returns a function for evaluating the probability density function (PDF) for a gamma distribution with shape parameter `alpha` and rate parameter `beta`.
+	* Returns a function for evaluating the probability density function (PDF) for an inverse gamma distribution with shape parameter `alpha` and rate parameter `beta`.
 	*
 	* @param alpha - shape parameter
 	* @param beta - rate parameter

lib/node_modules/@stdlib/stats/base/dists/invgamma/quantile/docs/types/index.d.ts

@@ -78,6 +78,7 @@ interface Quantile {
 	* @example
 	* // Non-positive shape parameter:
 	* var y = quantile( 0.5, -1.0, 1.0 );
+	* // returns NaN
 	*
 	* @example
 	* // Non-positive rate parameter:
@@ -109,7 +110,7 @@ interface Quantile {
 *
 * @param p - input value
 * @param alpha - shape parameter
-* @param beta - rate parameter
+* @param beta - scale parameter
 * @returns evaluated quantile function
 *
 * @example

lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/logcdf/docs/types/index.d.ts

@@ -89,11 +89,11 @@ interface LogCDF {
 	( x: number, a: number, b: number ): number;
 
 	/**
-	* Returns a function for evaluating the cumulative distribution function (CDF) for a Kumaraswamy's double bounded distribution with first shape parameter `a` and second shape parameter `b`.
+	* Returns a function for evaluating the natural logarithm of the cumulative distribution function (CDF) for a Kumaraswamy's double bounded distribution with first shape parameter `a` and second shape parameter `b`.
 	*
 	* @param a - first shape parameter
 	* @param b - second shape parameter
-	* @returns CDF
+	* @returns logCDF
 	*
 	* @example
 	* var mylogcdf = logcdf.factory( 0.5, 0.5 );

lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/logpdf/docs/types/index.d.ts

@@ -108,7 +108,7 @@ interface LogPDF {
 }
 
 /**
-* Arcsine distribution logarithm of probability density function (PDF).
+* Kumaraswamy's double bounded distribution logarithm of probability density function (PDF).
 *
 * @param x - input value
 * @param a - first shape parameter

lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/quantile/docs/types/index.d.ts

@@ -111,7 +111,7 @@ interface Quantile {
 /**
 * Kumaraswamy's double bounded distribution quantile function.
 *
-* @param x - input value
+* @param p - input probability
 * @param a - first shape parameter
 * @param b - second shape parameter
 * @returns evaluated quantile function

lib/node_modules/@stdlib/stats/base/dists/laplace/cdf/docs/types/index.d.ts

@@ -35,7 +35,7 @@ interface CDF {
 	*
 	* ## Notes
 	*
-	* -   If provided `b = < 0`, the function returns `NaN`.
+	* -   If provided `b < 0`, the function returns `NaN`.
 	*
 	* @param x - input value
 	* @param mu - location parameter