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Copy file name to clipboardExpand all lines: lib/node_modules/@stdlib/blas/ext/base/README.md
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<divclass="namespace-toc">
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- <spanclass="signature">[`cfill( N, alpha, x, strideX )`][@stdlib/blas/ext/base/cfill]</span><spanclass="delimiter">: </span><spanclass="description">fill a single-precision complex floating-point strided array with a specified scalar constant.</span>
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- <spanclass="signature">[`cindexOfColumn( order, M, N, A, LDA, x, strideX, workspace, strideW )`][@stdlib/blas/ext/base/cindex-of-column]</span><spanclass="delimiter">: </span><spanclass="description">return the index of the first column in a single-precision complex floating-point input matrix which has the same elements as a provided search vector.</span>
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- <spanclass="signature">[`cindexOfRow( order, M, N, A, LDA, x, strideX, workspace, strideW )`][@stdlib/blas/ext/base/cindex-of-row]</span><spanclass="delimiter">: </span><spanclass="description">return the index of the first row in a single-precision complex floating-point input matrix which has the same elements as a provided search vector.</span>
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- <spanclass="signature">[`cindexOf( N, searchElement, x, strideX )`][@stdlib/blas/ext/base/cindex-of]</span><spanclass="delimiter">: </span><spanclass="description">return the first index of a specified search element in a single-precision complex floating-point strided array.</span>
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- <spanclass="signature">[`clastIndexOfRow( order, M, N, A, LDA, x, strideX, workspace, strideW )`][@stdlib/blas/ext/base/clast-index-of-row]</span><spanclass="delimiter">: </span><spanclass="description">return the index of the last row in a single-precision complex floating-point input matrix which has the same elements as a provided search vector.</span>
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- <spanclass="signature">[`szeroTo( N, x, strideX )`][@stdlib/blas/ext/base/szero-to]</span><spanclass="delimiter">: </span><spanclass="description">fill a single-precision floating-point strided array with linearly spaced numeric elements which increment by `1` starting from zero.</span>
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- <spanclass="signature">[`wasm`][@stdlib/blas/ext/base/wasm]</span><spanclass="delimiter">: </span><spanclass="description">extensions to basic linear algebra subprograms (BLAS) compiled to WebAssembly.</span>
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- <spanclass="signature">[`zfill( N, alpha, x, strideX )`][@stdlib/blas/ext/base/zfill]</span><spanclass="delimiter">: </span><spanclass="description">fill a double-precision complex floating-point strided array with a specified scalar constant.</span>
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- <spanclass="signature">[`zindexOfColumn( order, M, N, A, LDA, x, strideX, workspace, strideW )`][@stdlib/blas/ext/base/zindex-of-column]</span><spanclass="delimiter">: </span><spanclass="description">return the index of the first column in a double-precision complex floating-point input matrix which has the same elements as a provided search vector.</span>
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- <spanclass="signature">[`zindexOfRow( order, M, N, A, LDA, x, strideX, workspace, strideW )`][@stdlib/blas/ext/base/zindex-of-row]</span><spanclass="delimiter">: </span><spanclass="description">return the index of the first row in a double-precision complex floating-point input matrix which has the same elements as a provided search vector.</span>
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- <spanclass="signature">[`zindexOf( N, searchElement, x, strideX )`][@stdlib/blas/ext/base/zindex-of]</span><spanclass="delimiter">: </span><spanclass="description">return the first index of a specified search element in a double-precision complex floating-point strided array.</span>
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- <spanclass="signature">[`zlastIndexOfRow( order, M, N, A, LDA, x, strideX, workspace, strideW )`][@stdlib/blas/ext/base/zlast-index-of-row]</span><spanclass="delimiter">: </span><spanclass="description">return the index of the last row in a double-precision complex floating-point input matrix which has the same elements as a provided search vector.</span>
Copy file name to clipboardExpand all lines: lib/node_modules/@stdlib/ndarray/README.md
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@@ -56,6 +56,7 @@ The namespace exports the following functions to create multidimensional arrays:
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- <spanclass="signature">[`scalar2ndarrayLike( x, value[, options] )`][@stdlib/ndarray/from-scalar-like]</span><spanclass="delimiter">: </span><spanclass="description">convert a scalar value to a zero-dimensional ndarray having the same data-type as a provided ndarray.</span>
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- <spanclass="signature">[`scalar2ndarray( value[, options] )`][@stdlib/ndarray/from-scalar]</span><spanclass="delimiter">: </span><spanclass="description">convert a scalar value to a zero-dimensional ndarray.</span>
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- <spanclass="signature">[`nansLike( x[, options] )`][@stdlib/ndarray/nans-like]</span><spanclass="delimiter">: </span><spanclass="description">create a NaN-filled ndarray having the same shape and data type as a provided ndarray.</span>
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- <spanclass="signature">[`nans( shape[, options] )`][@stdlib/ndarray/nans]</span><spanclass="delimiter">: </span><spanclass="description">create a NaN-filled ndarray having a specified shape and data type.</span>
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- <spanclass="signature">[`ndarraylike2ndarray( x[, options] )`][@stdlib/ndarray/ndarraylike2ndarray]</span><spanclass="delimiter">: </span><spanclass="description">convert an ndarray-like object to an `ndarray`.</span>
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- <spanclass="signature">[`onesLike( x[, options] )`][@stdlib/ndarray/ones-like]</span><spanclass="delimiter">: </span><spanclass="description">create a ones-filled ndarray having the same shape and data type as a provided ndarray.</span>
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- <spanclass="signature">[`ones( shape[, options] )`][@stdlib/ndarray/ones]</span><spanclass="delimiter">: </span><spanclass="description">create a ones-filled ndarray having a specified shape and data type.</span>
Copy file name to clipboardExpand all lines: lib/node_modules/@stdlib/stats/base/dists/discrete-uniform/README.md
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- <spanclass="signature">[`cdf( x, a, b )`][@stdlib/stats/base/dists/discrete-uniform/cdf]</span><spanclass="delimiter">: </span><spanclass="description">discrete uniform distribution cumulative distribution function.</span>
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- <spanclass="signature">[`logcdf( x, a, b )`][@stdlib/stats/base/dists/discrete-uniform/logcdf]</span><spanclass="delimiter">: </span><spanclass="description">evaluate the natural logarithm of the cumulative distribution function for a discrete uniform distribution.</span>
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- <spanclass="signature">[`logcdf( x, a, b )`][@stdlib/stats/base/dists/discrete-uniform/logcdf]</span><spanclass="delimiter">: </span><spanclass="description">discrete uniform distribution logarithm of cumulative distribution function.</span>
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- <spanclass="signature">[`logpmf( x, a, b )`][@stdlib/stats/base/dists/discrete-uniform/logpmf]</span><spanclass="delimiter">: </span><spanclass="description">evaluate the natural logarithm of the probability mass function (PMF) for a discrete uniform distribution.</span>
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- <spanclass="signature">[`mgf( t, a, b )`][@stdlib/stats/base/dists/discrete-uniform/mgf]</span><spanclass="delimiter">: </span><spanclass="description">discrete uniform distribution moment-generating function (MGF).</span>
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- <spanclass="signature">[`pmf( x, a, b )`][@stdlib/stats/base/dists/discrete-uniform/pmf]</span><spanclass="delimiter">: </span><spanclass="description">discrete uniform distribution probability mass function (PMF).</span>
Copy file name to clipboardExpand all lines: lib/node_modules/@stdlib/stats/base/dists/exponential/README.md
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- <spanclass="signature">[`cdf( x, lambda )`][@stdlib/stats/base/dists/exponential/cdf]</span><spanclass="delimiter">: </span><spanclass="description">exponential distribution cumulative distribution function.</span>
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- <spanclass="signature">[`logcdf( x, lambda )`][@stdlib/stats/base/dists/exponential/logcdf]</span><spanclass="delimiter">: </span><spanclass="description">evaluate the natural logarithm of the cumulative distribution function for an exponential distribution.</span>
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- <spanclass="signature">[`logcdf( x, lambda )`][@stdlib/stats/base/dists/exponential/logcdf]</span><spanclass="delimiter">: </span><spanclass="description">exponential distribution logarithm of cumulative distribution function.</span>
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- <spanclass="signature">[`logpdf( x, lambda )`][@stdlib/stats/base/dists/exponential/logpdf]</span><spanclass="delimiter">: </span><spanclass="description">evaluate the natural logarithm of the probability density function (PDF) for an exponential distribution.</span>
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- <spanclass="signature">[`mgf( t, lambda )`][@stdlib/stats/base/dists/exponential/mgf]</span><spanclass="delimiter">: </span><spanclass="description">exponential distribution moment-generating function (MGF).</span>
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- <spanclass="signature">[`pdf( x, lambda )`][@stdlib/stats/base/dists/exponential/pdf]</span><spanclass="delimiter">: </span><spanclass="description">exponential distribution probability density function (PDF).</span>
Copy file name to clipboardExpand all lines: lib/node_modules/@stdlib/stats/base/dists/pareto-type1/README.md
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- <spanclass="signature">[`cdf( x, alpha, beta )`][@stdlib/stats/base/dists/pareto-type1/cdf]</span><spanclass="delimiter">: </span><spanclass="description">Pareto (Type I) distribution cumulative distribution function.</span>
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- <spanclass="signature">[`logcdf( x, alpha, beta )`][@stdlib/stats/base/dists/pareto-type1/logcdf]</span><spanclass="delimiter">: </span><spanclass="description">evaluate the natural logarithm of the cumulative distribution function for a Pareto (Type I) distribution.</span>
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- <spanclass="signature">[`logcdf( x, alpha, beta )`][@stdlib/stats/base/dists/pareto-type1/logcdf]</span><spanclass="delimiter">: </span><spanclass="description">Pareto (Type I) distribution logarithm of cumulative distribution function.</span>
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- <spanclass="signature">[`logpdf( x, alpha, beta )`][@stdlib/stats/base/dists/pareto-type1/logpdf]</span><spanclass="delimiter">: </span><spanclass="description">evaluate the natural logarithm of the probability density function (PDF) for a Pareto (Type I) distribution.</span>
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- <spanclass="signature">[`pdf( x, alpha, beta )`][@stdlib/stats/base/dists/pareto-type1/pdf]</span><spanclass="delimiter">: </span><spanclass="description">Pareto (Type I) distribution probability density function (PDF).</span>
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