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Copy file name to clipboardExpand all lines: lib/node_modules/@stdlib/stats/base/README.md
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@@ -83,7 +83,7 @@ The namespace contains the following statistical functions:
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- <spanclass="signature">[`range( N, x, strideX )`][@stdlib/stats/base/range]</span><spanclass="delimiter">: </span><spanclass="description">calculate the range of a strided array.</span>
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- <spanclass="signature">[`sdsnanmean( N, x, stride )`][@stdlib/stats/base/sdsnanmean]</span><spanclass="delimiter">: </span><spanclass="description">calculate the arithmetic mean of a single-precision floating-point strided array, ignoring `NaN` values and using extended accumulation.</span>
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- <spanclass="signature">[`sdsnanmeanors( N, x, stride )`][@stdlib/stats/base/sdsnanmeanors]</span><spanclass="delimiter">: </span><spanclass="description">calculate the arithmetic mean of a single-precision floating-point strided array, ignoring `NaN` values and using ordinary recursive summation with extended accumulation.</span>
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- <spanclass="signature">[`smeankbn( N, x, stride )`][@stdlib/stats/base/smeankbn]</span><spanclass="delimiter">: </span><spanclass="description">calculate the arithmetic mean of a single-precision floating-point strided array using an improved Kahan–Babuška algorithm.</span>
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- <spanclass="signature">[`smeankbn( N, x, stride )`][@stdlib/stats/strided/smeankbn]</span><spanclass="delimiter">: </span><spanclass="description">calculate the arithmetic mean of a single-precision floating-point strided array using an improved Kahan–Babuška algorithm.</span>
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- <spanclass="signature">[`smeankbn2( N, x, stride )`][@stdlib/stats/strided/smeankbn2]</span><spanclass="delimiter">: </span><spanclass="description">calculate the arithmetic mean of a single-precision floating-point strided array using a second-order iterative Kahan–Babuška algorithm.</span>
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- <spanclass="signature">[`smeanlipw( N, x, stride )`][@stdlib/stats/strided/smeanlipw]</span><spanclass="delimiter">: </span><spanclass="description">calculate the arithmetic mean of a single-precision floating-point strided array using a one-pass trial mean algorithm with pairwise summation.</span>
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- <spanclass="signature">[`smeanors( N, x, stride )`][@stdlib/stats/strided/smeanors]</span><spanclass="delimiter">: </span><spanclass="description">calculate the arithmetic mean of a single-precision floating-point strided array using ordinary recursive summation.</span>
Copy file name to clipboardExpand all lines: lib/node_modules/@stdlib/stats/strided/dmeankbn/README.md
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- <span class="package-name">[`@stdlib/stats/strided/dmean`][@stdlib/stats/strided/dmean]</span><span class="delimiter">: </span><span class="description">calculate the arithmetic mean of a double-precision floating-point strided array.</span>
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- <span class="package-name">[`@stdlib/stats/strided/meankbn`][@stdlib/stats/strided/meankbn]</span><span class="delimiter">: </span><span class="description">calculate the arithmetic mean of a strided array using an improved Kahan–Babuška algorithm.</span>
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- <span class="package-name">[`@stdlib/stats/base/smeankbn`][@stdlib/stats/base/smeankbn]</span><span class="delimiter">: </span><span class="description">calculate the arithmetic mean of a single-precision floating-point strided array using an improved Kahan–Babuška algorithm.</span>
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- <span class="package-name">[`@stdlib/stats/strided/smeankbn`][@stdlib/stats/strided/smeankbn]</span><span class="delimiter">: </span><span class="description">calculate the arithmetic mean of a single-precision floating-point strided array using an improved Kahan–Babuška algorithm.</span>
Copy file name to clipboardExpand all lines: lib/node_modules/@stdlib/stats/strided/meankbn/README.md
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@@ -125,7 +125,7 @@ var v = meankbn.ndarray( 4, x, 2, 1 );
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- If `N <= 0`, both functions return `NaN`.
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- Both functions support array-like objects having getter and setter accessors for array element access (e.g., [`@stdlib/array/base/accessor`][@stdlib/array/base/accessor]).
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- Depending on the environment, the typed versions ([`dmeankbn`][@stdlib/stats/strided/dmeankbn], [`smeankbn`][@stdlib/stats/base/smeankbn], etc.) are likely to be significantly more performant.
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- Depending on the environment, the typed versions ([`dmeankbn`][@stdlib/stats/strided/dmeankbn], [`smeankbn`][@stdlib/stats/strided/smeankbn], etc.) are likely to be significantly more performant.
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</section>
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@@ -176,7 +176,7 @@ console.log( v );
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- <spanclass="package-name">[`@stdlib/stats/strided/dmeankbn`][@stdlib/stats/strided/dmeankbn]</span><spanclass="delimiter">: </span><spanclass="description">calculate the arithmetic mean of a double-precision floating-point strided array using an improved Kahan–Babuška algorithm.</span>
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- <spanclass="package-name">[`@stdlib/stats/strided/mean`][@stdlib/stats/strided/mean]</span><spanclass="delimiter">: </span><spanclass="description">calculate the arithmetic mean of a strided array.</span>
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- <spanclass="package-name">[`@stdlib/stats/base/smeankbn`][@stdlib/stats/base/smeankbn]</span><spanclass="delimiter">: </span><spanclass="description">calculate the arithmetic mean of a single-precision floating-point strided array using an improved Kahan–Babuška algorithm.</span>
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- <spanclass="package-name">[`@stdlib/stats/strided/smeankbn`][@stdlib/stats/strided/smeankbn]</span><spanclass="delimiter">: </span><spanclass="description">calculate the arithmetic mean of a single-precision floating-point strided array using an improved Kahan–Babuška algorithm.</span>
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