docs: update REPL namespace documentation

PR-URL: #6802
Reviewed-by: Athan Reines <[email protected]>

Author: stdlib-bot

lib/node_modules/@stdlib/repl/help/data/data.csv

@@ -306,7 +306,7 @@ base.dists.arcsine.skewness,"\nbase.dists.arcsine.skewness( a, b )\n    Returns
 base.dists.arcsine.stdev,"\nbase.dists.arcsine.stdev( a, b )\n    Returns the standard deviation of an arcsine distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `a >= b`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var v = base.dists.arcsine.stdev( 0.0, 1.0 )\n    ~0.354\n    > v = base.dists.arcsine.stdev( 4.0, 12.0 )\n    ~2.828\n    > v = base.dists.arcsine.stdev( 2.0, 8.0 )\n    ~2.121\n\n"
 base.dists.arcsine.variance,"\nbase.dists.arcsine.variance( a, b )\n    Returns the variance of an arcsine distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `a >= b`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var v = base.dists.arcsine.variance( 0.0, 1.0 )\n    ~0.125\n    > v = base.dists.arcsine.variance( 4.0, 12.0 )\n    8.0\n    > v = base.dists.arcsine.variance( 2.0, 8.0 )\n    ~4.5\n\n"
 base.dists.bernoulli.Bernoulli,"\nbase.dists.bernoulli.Bernoulli( [p] )\n    Returns a Bernoulli distribution object.\n\n    Parameters\n    ----------\n    p: number (optional)\n        Success probability. Must be between `0` and `1`. Default: `0.5`.\n\n    Returns\n    -------\n    bernoulli: Object\n        Distribution instance.\n\n    bernoulli.p: number\n        Success probability. If set, the value must be between `0` and `1`.\n\n    bernoulli.entropy: number\n        Read-only property which returns the differential entropy.\n\n    bernoulli.kurtosis: number\n        Read-only property which returns the excess kurtosis.\n\n    bernoulli.mean: number\n        Read-only property which returns the expected value.\n\n    bernoulli.median: number\n        Read-only property which returns the median.\n\n    bernoulli.skewness: number\n        Read-only property which returns the skewness.\n\n    bernoulli.stdev: number\n        Read-only property which returns the standard deviation.\n\n    bernoulli.variance: number\n        Read-only property which returns the variance.\n\n    bernoulli.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    bernoulli.mgf: Function\n        Evaluates the moment-generating function (MGF).\n\n    bernoulli.pmf: Function\n        Evaluates the probability mass function (PMF).\n\n    bernoulli.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var bernoulli = base.dists.bernoulli.Bernoulli( 0.6 );\n    > bernoulli.p\n    0.6\n    > bernoulli.entropy\n    ~0.673\n    > bernoulli.kurtosis\n    ~-1.833\n    > bernoulli.mean\n    0.6\n    > bernoulli.median\n    1.0\n    > bernoulli.skewness\n    ~-0.408\n    > bernoulli.stdev\n    ~0.49\n    > bernoulli.variance\n    ~0.24\n    > bernoulli.cdf( 0.5 )\n    0.4\n    > bernoulli.mgf( 3.0 )\n    ~12.451\n    > bernoulli.pmf( 0.0 )\n    0.4\n    > bernoulli.quantile( 0.7 )\n    1.0\n\n"
-base.dists.bernoulli.cdf,"\nbase.dists.bernoulli.cdf( x, p )\n    Evaluates the cumulative distribution function (CDF) for a Bernoulli\n    distribution with success probability `p` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.bernoulli.cdf( 0.5, 0.5 )\n    0.5\n    > y = base.dists.bernoulli.cdf( 0.8, 0.1 )\n    0.9\n    > y = base.dists.bernoulli.cdf( -1.0, 0.4 )\n    0.0\n    > y = base.dists.bernoulli.cdf( 1.5, 0.4 )\n    1.0\n    > y = base.dists.bernoulli.cdf( NaN, 0.5 )\n    NaN\n    > y = base.dists.bernoulli.cdf( 0.0, NaN )\n    NaN\n    // Invalid probability:\n    > y = base.dists.bernoulli.cdf( 2.0, 1.4 )\n    NaN\n\n\nbase.dists.bernoulli.cdf.factory( p )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Bernoulli distribution with success probability `p`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.bernoulli.cdf.factory( 0.5 );\n    > var y = mycdf( 3.0 )\n    1.0\n    > y = mycdf( 0.7 )\n    0.5\n\n"
+base.dists.bernoulli.cdf,"\nbase.dists.bernoulli.cdf( x, p )\n    Evaluates the cumulative distribution function (CDF) for a Bernoulli\n    distribution with success probability `p`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.bernoulli.cdf( 0.5, 0.5 )\n    0.5\n    > y = base.dists.bernoulli.cdf( 0.8, 0.1 )\n    0.9\n    > y = base.dists.bernoulli.cdf( -1.0, 0.4 )\n    0.0\n    > y = base.dists.bernoulli.cdf( 1.5, 0.4 )\n    1.0\n    > y = base.dists.bernoulli.cdf( NaN, 0.5 )\n    NaN\n    > y = base.dists.bernoulli.cdf( 0.0, NaN )\n    NaN\n    // Invalid probability:\n    > y = base.dists.bernoulli.cdf( 2.0, 1.4 )\n    NaN\n\n\nbase.dists.bernoulli.cdf.factory( p )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Bernoulli distribution with success probability `p`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.bernoulli.cdf.factory( 0.5 );\n    > var y = mycdf( 3.0 )\n    1.0\n    > y = mycdf( 0.7 )\n    0.5\n\n"
 base.dists.bernoulli.cdf.factory,"\nbase.dists.bernoulli.cdf.factory( p )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Bernoulli distribution with success probability `p`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.bernoulli.cdf.factory( 0.5 );\n    > var y = mycdf( 3.0 )\n    1.0\n    > y = mycdf( 0.7 )\n    0.5"
 base.dists.bernoulli.entropy,"\nbase.dists.bernoulli.entropy( p )\n    Returns the entropy of a Bernoulli distribution with success probability\n    `p` (in nats).\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Entropy.\n\n    Examples\n    --------\n    > var v = base.dists.bernoulli.entropy( 0.1 )\n    ~0.325\n    > v = base.dists.bernoulli.entropy( 0.5 )\n    ~0.693\n\n"
 base.dists.bernoulli.kurtosis,"\nbase.dists.bernoulli.kurtosis( p )\n    Returns the excess kurtosis of a Bernoulli distribution with success\n    probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Excess kurtosis.\n\n    Examples\n    --------\n    > var v = base.dists.bernoulli.kurtosis( 0.1 )\n    ~5.111\n    > v = base.dists.bernoulli.kurtosis( 0.5 )\n    -2.0\n\n"

lib/node_modules/@stdlib/repl/help/data/data.json

@@ -306,7 +306,7 @@ base.dists.arcsine.skewness,"\nbase.dists.arcsine.skewness( a:number, b:number )
 base.dists.arcsine.stdev,"\nbase.dists.arcsine.stdev( a:number, b:number )\n    Returns the standard deviation of an arcsine distribution.\n"
 base.dists.arcsine.variance,"\nbase.dists.arcsine.variance( a:number, b:number )\n    Returns the variance of an arcsine distribution.\n"
 base.dists.bernoulli.Bernoulli,"\nbase.dists.bernoulli.Bernoulli( [p:number] )\n    Returns a Bernoulli distribution object.\n"
-base.dists.bernoulli.cdf,"\nbase.dists.bernoulli.cdf( x:number, p:number )\n    Evaluates the cumulative distribution function (CDF) for a Bernoulli\n    distribution with success probability `p` at a value `x`.\n"
+base.dists.bernoulli.cdf,"\nbase.dists.bernoulli.cdf( x:number, p:number )\n    Evaluates the cumulative distribution function (CDF) for a Bernoulli\n    distribution with success probability `p`.\n"
 base.dists.bernoulli.cdf.factory,"\nbase.dists.bernoulli.cdf.factory( p:number )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Bernoulli distribution with success probability `p`.\n"
 base.dists.bernoulli.entropy,"\nbase.dists.bernoulli.entropy( p:number )\n    Returns the entropy of a Bernoulli distribution with success probability\n    `p` (in nats).\n"
 base.dists.bernoulli.kurtosis,"\nbase.dists.bernoulli.kurtosis( p:number )\n    Returns the excess kurtosis of a Bernoulli distribution with success\n    probability `p`.\n"