diff --git a/lib/node_modules/@stdlib/repl/info/data/data.csv b/lib/node_modules/@stdlib/repl/info/data/data.csv index 29efc0425152..6ee3846a0441 100644 --- a/lib/node_modules/@stdlib/repl/info/data/data.csv +++ b/lib/node_modules/@stdlib/repl/info/data/data.csv @@ -2564,7 +2564,7 @@ base.wrap,"\nbase.wrap( v:number, min:number, max:number )\n Wraps a value to base.xlog1py,"\nbase.xlog1py( x:number, y:number )\n Computes `x * ln(y+1)` so that the result is `0` if `x = 0`.\n" base.xlogy,"\nbase.xlogy( x:number, y:number )\n Computes `x * ln(y)` so that the result is `0` if `x = 0`.\n" base.zeta,"\nbase.zeta( s:number )\n Evaluates the Riemann zeta function as a function of a real variable `s`.\n" -BERNDT_CPS_WAGES_1985,"\nBERNDT_CPS_WAGES_1985()\n Returns a random sample of 534 workers from the Current Population Survey\n (CPS) from 1985, including their wages and and other characteristics.\n" +BERNDT_CPS_WAGES_1985,"\nBERNDT_CPS_WAGES_1985()\n Returns a random sample of 534 workers from the Current Population Survey\n (CPS) from 1985, including their wages and other characteristics.\n" bifurcate,"\nbifurcate( collection:Array|TypedArray|Object, [options:Object,] \n filter:Array|TypedArray|Object )\n Splits values into two groups.\n" bifurcateBy,"\nbifurcateBy( collection:Array|TypedArray|Object, [options:Object,] \n predicate:Function )\n Splits values into two groups according to a predicate function.\n" bifurcateByAsync,"\nbifurcateByAsync( collection:Array|TypedArray|Object, [options:Object,] \n predicate:Function, done:Function )\n Splits values into two groups according to a predicate function.\n" diff --git a/lib/node_modules/@stdlib/stats/base/dists/arcsine/mode/README.md b/lib/node_modules/@stdlib/stats/base/dists/arcsine/mode/README.md index c51d6f5e5b37..ac7bbb3b6f8f 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/arcsine/mode/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/arcsine/mode/README.md @@ -26,7 +26,7 @@ limitations under the License.
-The [mode][mode] for an [arcsine][arcsine-distribution] random variable with with minimum support `a` and maximum support `b` is +The [mode][mode] for an [arcsine][arcsine-distribution] random variable with minimum support `a` and maximum support `b` is diff --git a/lib/node_modules/@stdlib/stats/base/dists/arcsine/skewness/README.md b/lib/node_modules/@stdlib/stats/base/dists/arcsine/skewness/README.md index 0029f60ef110..22019508d19f 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/arcsine/skewness/README.md +++ b/lib/node_modules/@stdlib/stats/base/dists/arcsine/skewness/README.md @@ -26,7 +26,7 @@ limitations under the License.
-The [skewness][skewness] for an [arcsine][arcsine-distribution] random variable with with minimum support `a` and maximum support `b` is +The [skewness][skewness] for an [arcsine][arcsine-distribution] random variable with minimum support `a` and maximum support `b` is diff --git a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/ctor/lib/main.js b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/ctor/lib/main.js index 35b7bb279209..12fe8191b363 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/ctor/lib/main.js +++ b/lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/ctor/lib/main.js @@ -56,7 +56,7 @@ function discreteUniformCDF( x ) { } /** -* Evaluates the the natural logarithm of the cumulative distribution function (logCDF). +* Evaluates the natural logarithm of the cumulative distribution function (logCDF). * * @private * @param {number} x - input value diff --git a/lib/node_modules/@stdlib/stats/base/dists/uniform/ctor/lib/main.js b/lib/node_modules/@stdlib/stats/base/dists/uniform/ctor/lib/main.js index 61ae1ef2774a..5617f878b1fd 100644 --- a/lib/node_modules/@stdlib/stats/base/dists/uniform/ctor/lib/main.js +++ b/lib/node_modules/@stdlib/stats/base/dists/uniform/ctor/lib/main.js @@ -57,7 +57,7 @@ function uniformCDF( x ) { } /** -* Evaluates the the natural logarithm of the cumulative distribution function (logCDF). +* Evaluates the natural logarithm of the cumulative distribution function (logCDF). * * @private * @param {number} x - input value