docs: use displaystyle in fractions with summation symbol

lib/node_modules/@stdlib/stats/bartlett-test/README.md

@@ -28,13 +28,13 @@ Bartlett's test is used to test the null hypothesis that the variances of k grou
 
 For `k` groups each with `n_i` observations, the test statistic is
 
-<!-- <equation class="equation" label="eq:bartlett-test-statistic" align="center" raw="\chi^2 = \frac{N\ln(S^2) - \sum_{i=0}^{k-1} n_i \ln(S_i^2)}{1 + \frac{1}{3(k-1)}\left(\sum_{i=0}^{k-1} \frac{1}{n_i} - \frac{1}{N}\right)}" alt="Equation for Bartlett's test statistic."> -->
+<!-- <equation class="equation" label="eq:bartlett-test-statistic" align="center" raw="\chi^2 = \frac{\displaystyle N\ln(S^2) - \sum_{i=0}^{k-1} n_i \ln(S_i^2)}{\displaystyle 1 + \frac{1}{3(k-1)}\left(\sum_{i=0}^{k-1} \frac{1}{n_i} - \frac{1}{N}\right)}" alt="Equation for Bartlett's test statistic."> -->
 
 ```math
-\chi^2 = \frac{N\ln(S^2) - \sum_{i=0}^{k-1} n_i \ln(S_i^2)}{1 + \frac{1}{3(k-1)}\left(\sum_{i=0}^{k-1} \frac{1}{n_i} - \frac{1}{N}\right)}
+\chi^2 = \frac{\displaystyle N\ln(S^2) - \sum_{i=0}^{k-1} n_i \ln(S_i^2)}{\displaystyle 1 + \frac{1}{3(k-1)}\left(\sum_{i=0}^{k-1} \frac{1}{n_i} - \frac{1}{N}\right)}
 ```
 
-<!-- <div class="equation" align="center" data-raw-text="\chi^2 = \frac{N\ln(S^2) - \sum_{i=0}^{k-1} n_i \ln(S_i^2)}{1 + \frac{1}{3(k-1)}\left(\sum_{i=0}^{k-1} \frac{1}{n_i} - \frac{1}{N}\right)}" data-equation="eq:bartlett-test-statistic">
+<!-- <div class="equation" align="center" data-raw-text="\chi^2 = \frac{\displaystyle N\ln(S^2) - \sum_{i=0}^{k-1} n_i \ln(S_i^2)}{\displaystyle 1 + \frac{1}{3(k-1)}\left(\sum_{i=0}^{k-1} \frac{1}{n_i} - \frac{1}{N}\right)}" data-equation="eq:bartlett-test-statistic">
     <img src="https://cdn.jsdelivr.net/gh/stdlib-js/stdlib@4b1db4ebd815eb54bf53a3fa132b992604743d9c/lib/node_modules/@stdlib/stats/bartlett-test/docs/img/equation_bartlett-test-statistic.svg" alt="Equation for Bartlett's test statistic.">
     <br>
 </div> -->

lib/node_modules/@stdlib/stats/incr/apcorr/README.md

@@ -43,13 +43,13 @@ where the numerator is the [covariance][covariance] and the denominator is the p
 
 For a sample of size `n`, the sample [Pearson product-moment correlation coefficient][pearson-correlation] is defined as
 
-<!-- <equation class="equation" label="eq:sample_pearson_correlation_coefficient" align="center" raw="r = \frac{\sum_{i=0}^{n-1} (x_i - \bar{x})(y_i - \bar{y})}{\sqrt{\sum_{i=0}^{n-1} (x_i - \bar{x})^2} \sqrt{\sum_{i=0}^{n-1} (y_i - \bar{y})^2}}" alt="Equation for the sample Pearson product-moment correlation coefficient."> -->
+<!-- <equation class="equation" label="eq:sample_pearson_correlation_coefficient" align="center" raw="r = \frac{\displaystyle\sum_{i=0}^{n-1} (x_i - \bar{x})(y_i - \bar{y})}{\displaystyle\sqrt{\sum_{i=0}^{n-1} (x_i - \bar{x})^2} \sqrt{\sum_{i=0}^{n-1} (y_i - \bar{y})^2}}" alt="Equation for the sample Pearson product-moment correlation coefficient."> -->
 
 ```math
-r = \frac{\sum_{i=0}^{n-1} (x_i - \bar{x})(y_i - \bar{y})}{\sqrt{\sum_{i=0}^{n-1} (x_i - \bar{x})^2} \sqrt{\sum_{i=0}^{n-1} (y_i - \bar{y})^2}}
+r = \frac{\displaystyle\sum_{i=0}^{n-1} (x_i - \bar{x})(y_i - \bar{y})}{\displaystyle\sqrt{\sum_{i=0}^{n-1} (x_i - \bar{x})^2} \sqrt{\sum_{i=0}^{n-1} (y_i - \bar{y})^2}}
 ```
 
-<!-- <div class="equation" align="center" data-raw-text="r = \frac{\sum_{i=0}^{n-1} (x_i - \bar{x})(y_i - \bar{y})}{\sqrt{\sum_{i=0}^{n-1} (x_i - \bar{x})^2} \sqrt{\sum_{i=0}^{n-1} (y_i - \bar{y})^2}}" data-equation="eq:sample_pearson_correlation_coefficient">
+<!-- <div class="equation" align="center" data-raw-text="r = \frac{\displaystyle\sum_{i=0}^{n-1} (x_i - \bar{x})(y_i - \bar{y})}{\displaystyle\sqrt{\sum_{i=0}^{n-1} (x_i - \bar{x})^2} \sqrt{\sum_{i=0}^{n-1} (y_i - \bar{y})^2}}" data-equation="eq:sample_pearson_correlation_coefficient">
     <img src="https://cdn.jsdelivr.net/gh/stdlib-js/stdlib@80f96253bf726f33bc71d8eb68037ab203ae4cf9/lib/node_modules/@stdlib/stats/incr/apcorr/docs/img/equation_sample_pearson_correlation_coefficient.svg" alt="Equation for the sample Pearson product-moment correlation coefficient.">
     <br>
 </div> -->

lib/node_modules/@stdlib/stats/incr/hmean/README.md

@@ -26,13 +26,13 @@ limitations under the License.
 
 The [harmonic mean][harmonic-mean] of positive real numbers `x_0, x_1, ..., x_{n-1}` is defined as
 
-<!-- <equation class="equation" label="eq:harmonic_mean" align="center" raw="\begin{align}H &= \frac{n}{\frac{1}{x_0} + \frac{1}{x_1} + \cdots + \frac{1}{x_{n-1}}} \\ &= \frac{n}{\sum_{i=0}^{n-1} \frac{1}{x_i}} \\ &= \biggl( \frac{\sum_{i=0}^{n-1} \frac{1}{x_i}}{n} \biggr)^{-1}\end{align}" alt="Equation for the harmonic mean."> -->
+<!-- <equation class="equation" label="eq:harmonic_mean" align="center" raw="\begin{align}H &= \frac{n}{\frac{1}{x_0} + \frac{1}{x_1} + \cdots + \frac{1}{x_{n-1}}} \\ &= \frac{\displaystyle n}{\displaystyle\sum_{i=0}^{n-1} \frac{1}{x_i}} \\ &= \biggl( \frac{\displaystyle\sum_{i=0}^{n-1} \frac{1}{x_i}}{\displaystyle n} \biggr)^{-1}\end{align}" alt="Equation for the harmonic mean."> -->
 
 ```math
-\begin{align}H &= \frac{n}{\frac{1}{x_0} + \frac{1}{x_1} + \cdots + \frac{1}{x_{n-1}}} \\ &= \frac{n}{\sum_{i=0}^{n-1} \frac{1}{x_i}} \\ &= \biggl( \frac{\sum_{i=0}^{n-1} \frac{1}{x_i}}{n} \biggr)^{-1}\end{align}
+\begin{align}H &= \frac{n}{\frac{1}{x_0} + \frac{1}{x_1} + \cdots + \frac{1}{x_{n-1}}} \\ &= \frac{\displaystyle n}{\displaystyle\sum_{i=0}^{n-1} \frac{1}{x_i}} \\ &= \biggl( \frac{\displaystyle\sum_{i=0}^{n-1} \frac{1}{x_i}}{\displaystyle n} \biggr)^{-1}\end{align}
 ```
 
-<!-- <div class="equation" align="center" data-raw-text="\begin{align}H &amp;= \frac{n}{\frac{1}{x_0} + \frac{1}{x_1} + \cdots + \frac{1}{x_{n-1}}} \\ &amp;= \frac{n}{\sum_{i=0}^{n-1} \frac{1}{x_i}} \\ &amp;= \biggl( \frac{\sum_{i=0}^{n-1} \frac{1}{x_i}}{n} \biggr)^{-1}\end{align}" data-equation="eq:harmonic_mean">
+<!-- <div class="equation" align="center" data-raw-text="\begin{align}H &amp;= \frac{n}{\frac{1}{x_0} + \frac{1}{x_1} + \cdots + \frac{1}{x_{n-1}}} \\ &amp;= \frac{\displaystyle n}{\displaystyle\sum_{i=0}^{n-1} \frac{1}{x_i}} \\ &amp;= \biggl( \frac{\displaystyle\sum_{i=0}^{n-1} \frac{1}{x_i}}{\displaystyle n} \biggr)^{-1}\end{align}" data-equation="eq:harmonic_mean">
     <img src="https://cdn.jsdelivr.net/gh/stdlib-js/stdlib@2b632747053b9e357a4663369528fe62b29a6d55/lib/node_modules/@stdlib/stats/incr/hmean/docs/img/equation_harmonic_mean.svg" alt="Equation for the harmonic mean.">
     <br>
 </div> -->

lib/node_modules/@stdlib/stats/incr/kurtosis/README.md

@@ -60,13 +60,13 @@ where `m_4` is the sample fourth central moment and `m_2` is the sample second c
 
 The previous equation is, however, a biased estimator of the population excess kurtosis. An alternative estimator which is unbiased under normality is
 
-<!-- <equation class="equation" label="eq:corrected_sample_excess_kurtosis" align="center" raw="G_2 = \frac{(n+1)n}{(n-1)(n-2)(n-3)} \frac{\sum_{i=0}^{n-1} (x_i - \bar{x})^4}{\biggl(\sum_{i=0}^{n-1} (x_i - \bar{x})^2\biggr)^2} - 3 \frac{(n-1)^2}{(n-2)(n-3)}" alt="Equation for the corrected sample excess kurtosis."> -->
+<!-- <equation class="equation" label="eq:corrected_sample_excess_kurtosis" align="center" raw="G_2 = \frac{(n+1)n}{(n-1)(n-2)(n-3)} \frac{\displaystyle\sum_{i=0}^{n-1} (x_i - \bar{x})^4}{\biggl(\sum_{i=0}^{n-1} (x_i - \bar{x})^2\biggr)^2} - 3 \frac{(n-1)^2}{(n-2)(n-3)}" alt="Equation for the corrected sample excess kurtosis."> -->
 
 ```math
-G_2 = \frac{(n+1)n}{(n-1)(n-2)(n-3)} \frac{\sum_{i=0}^{n-1} (x_i - \bar{x})^4}{\biggl(\sum_{i=0}^{n-1} (x_i - \bar{x})^2\biggr)^2} - 3 \frac{(n-1)^2}{(n-2)(n-3)}
+G_2 = \frac{(n+1)n}{(n-1)(n-2)(n-3)} \frac{\displaystyle\sum_{i=0}^{n-1} (x_i - \bar{x})^4}{\biggl(\sum_{i=0}^{n-1} (x_i - \bar{x})^2\biggr)^2} - 3 \frac{(n-1)^2}{(n-2)(n-3)}
 ```
 
-<!-- <div class="equation" align="center" data-raw-text="G_2 = \frac{(n+1)n}{(n-1)(n-2)(n-3)} \frac{\sum_{i=0}^{n-1} (x_i - \bar{x})^4}{\biggl(\sum_{i=0}^{n-1} (x_i - \bar{x})^2\biggr)^2} - 3 \frac{(n-1)^2}{(n-2)(n-3)}" data-equation="eq:corrected_sample_excess_kurtosis">
+<!-- <div class="equation" align="center" data-raw-text="G_2 = \frac{(n+1)n}{(n-1)(n-2)(n-3)} \frac{\displaystyle\sum_{i=0}^{n-1} (x_i - \bar{x})^4}{\biggl(\sum_{i=0}^{n-1} (x_i - \bar{x})^2\biggr)^2} - 3 \frac{(n-1)^2}{(n-2)(n-3)}" data-equation="eq:corrected_sample_excess_kurtosis">
     <img src="https://cdn.jsdelivr.net/gh/stdlib-js/stdlib@49d8cabda84033d55d7b8069f19ee3dd8b8d1496/lib/node_modules/@stdlib/stats/incr/kurtosis/docs/img/equation_corrected_sample_excess_kurtosis.svg" alt="Equation for the corrected sample excess kurtosis.">
     <br>
 </div> -->

lib/node_modules/@stdlib/stats/incr/mae/README.md

@@ -26,13 +26,13 @@ limitations under the License.
 
 The [mean absolute error][mean-absolute-error] is defined as
 
-<!-- <equation class="equation" label="eq:mean_absolute_error" align="center" raw="\operatorname{MAE}  = \frac{\sum_{i=0}^{n-1} |y_i - x_i|}{n}" alt="Equation for the mean absolute error."> -->
+<!-- <equation class="equation" label="eq:mean_absolute_error" align="center" raw="\operatorname{MAE}  = \frac{\displaystyle\sum_{i=0}^{n-1} |y_i - x_i|}{n}" alt="Equation for the mean absolute error."> -->
 
 ```math
-\operatorname{MAE}  = \frac{\sum_{i=0}^{n-1} |y_i - x_i|}{n}
+\operatorname{MAE}  = \frac{\displaystyle\sum_{i=0}^{n-1} |y_i - x_i|}{n}
 ```
 
-<!-- <div class="equation" align="center" data-raw-text="\operatorname{MAE}  = \frac{\sum_{i=0}^{n-1} |y_i - x_i|}{n}" data-equation="eq:mean_absolute_error">
+<!-- <div class="equation" align="center" data-raw-text="\operatorname{MAE}  = \frac{\displaystyle\sum_{i=0}^{n-1} |y_i - x_i|}{n}" data-equation="eq:mean_absolute_error">
     <img src="https://cdn.jsdelivr.net/gh/stdlib-js/stdlib@49d8cabda84033d55d7b8069f19ee3dd8b8d1496/lib/node_modules/@stdlib/stats/incr/mae/docs/img/equation_mean_absolute_error.svg" alt="Equation for the mean absolute error.">
     <br>
 </div> -->

lib/node_modules/@stdlib/stats/incr/mapcorr/README.md

@@ -43,13 +43,13 @@ where the numerator is the [covariance][covariance] and the denominator is the p
 
 For a sample of size `W`, the sample [Pearson product-moment correlation coefficient][pearson-correlation] is defined as
 
-<!-- <equation class="equation" label="eq:sample_pearson_correlation_coefficient" align="center" raw="r = \frac{\sum_{i=0}^{n-1} (x_i - \bar{x})(y_i - \bar{y})}{\sqrt{\sum_{i=0}^{n-1} (x_i - \bar{x})^2} \sqrt{\sum_{i=0}^{n-1} (y_i - \bar{y})^2}}" alt="Equation for the sample Pearson product-moment correlation coefficient."> -->
+<!-- <equation class="equation" label="eq:sample_pearson_correlation_coefficient" align="center" raw="r = \frac{\displaystyle\sum_{i=0}^{n-1} (x_i - \bar{x})(y_i - \bar{y})}{\displaystyle\sqrt{\sum_{i=0}^{n-1} (x_i - \bar{x})^2} \sqrt{\sum_{i=0}^{n-1} (y_i - \bar{y})^2}}" alt="Equation for the sample Pearson product-moment correlation coefficient."> -->
 
 ```math
-r = \frac{\sum_{i=0}^{n-1} (x_i - \bar{x})(y_i - \bar{y})}{\sqrt{\sum_{i=0}^{n-1} (x_i - \bar{x})^2} \sqrt{\sum_{i=0}^{n-1} (y_i - \bar{y})^2}}
+r = \frac{\displaystyle\sum_{i=0}^{n-1} (x_i - \bar{x})(y_i - \bar{y})}{\displaystyle\sqrt{\sum_{i=0}^{n-1} (x_i - \bar{x})^2} \sqrt{\sum_{i=0}^{n-1} (y_i - \bar{y})^2}}
 ```
 
-<!-- <div class="equation" align="center" data-raw-text="r = \frac{\sum_{i=0}^{n-1} (x_i - \bar{x})(y_i - \bar{y})}{\sqrt{\sum_{i=0}^{n-1} (x_i - \bar{x})^2} \sqrt{\sum_{i=0}^{n-1} (y_i - \bar{y})^2}}" data-equation="eq:sample_pearson_correlation_coefficient">
+<!-- <div class="equation" align="center" data-raw-text="r = \frac{\displaystyle\sum_{i=0}^{n-1} (x_i - \bar{x})(y_i - \bar{y})}{\displaystyle\sqrt{\sum_{i=0}^{n-1} (x_i - \bar{x})^2} \sqrt{\sum_{i=0}^{n-1} (y_i - \bar{y})^2}}" data-equation="eq:sample_pearson_correlation_coefficient">
     <img src="https://cdn.jsdelivr.net/gh/stdlib-js/stdlib@e7c0cbc398c5e64614baf47cf5c6259b93c0ffce/lib/node_modules/@stdlib/stats/incr/mapcorr/docs/img/equation_sample_pearson_correlation_coefficient.svg" alt="Equation for the sample Pearson product-moment correlation coefficient.">
     <br>
 </div> -->

lib/node_modules/@stdlib/stats/incr/mhmean/README.md

@@ -26,13 +26,13 @@ limitations under the License.
 
 The [harmonic mean][harmonic-mean] of positive real numbers `x_0, x_1, ..., x_{n-1}` is defined as
 
-<!-- <equation class="equation" label="eq:harmonic_mean" align="center" raw="\begin{align}H &= \frac{n}{\frac{1}{x_0} + \frac{1}{x_1} + \cdots + \frac{1}{x_{n-1}}} \\ &= \frac{n}{\sum_{i=0}^{n-1} \frac{1}{x_i}} \\ &= \biggl( \frac{\sum_{i=0}^{n-1} \frac{1}{x_i}}{n} \biggr)^{-1}\end{align}" alt="Equation for the harmonic mean."> -->
+<!-- <equation class="equation" label="eq:harmonic_mean" align="center" raw="\begin{align}H &= \frac{n}{\frac{1}{x_0} + \frac{1}{x_1} + \cdots + \frac{1}{x_{n-1}}} \\ &= \frac{n}{\sum_{i=0}^{n-1} \frac{1}{x_i}} \\ &= \biggl( \frac{\displaystyle\sum_{i=0}^{n-1} \frac{1}{x_i}}{n} \biggr)^{-1}\end{align}" alt="Equation for the harmonic mean."> -->
 
 ```math
-\begin{align}H &= \frac{n}{\frac{1}{x_0} + \frac{1}{x_1} + \cdots + \frac{1}{x_{n-1}}} \\ &= \frac{n}{\sum_{i=0}^{n-1} \frac{1}{x_i}} \\ &= \biggl( \frac{\sum_{i=0}^{n-1} \frac{1}{x_i}}{n} \biggr)^{-1}\end{align}
+\begin{align}H &= \frac{n}{\frac{1}{x_0} + \frac{1}{x_1} + \cdots + \frac{1}{x_{n-1}}} \\ &= \frac{n}{\sum_{i=0}^{n-1} \frac{1}{x_i}} \\ &= \biggl( \frac{\displaystyle\sum_{i=0}^{n-1} \frac{1}{x_i}}{n} \biggr)^{-1}\end{align}
 ```
 
-<!-- <div class="equation" align="center" data-raw-text="\begin{align}H &amp;= \frac{n}{\frac{1}{x_0} + \frac{1}{x_1} + \cdots + \frac{1}{x_{n-1}}} \\ &amp;= \frac{n}{\sum_{i=0}^{n-1} \frac{1}{x_i}} \\ &amp;= \biggl( \frac{\sum_{i=0}^{n-1} \frac{1}{x_i}}{n} \biggr)^{-1}\end{align}" data-equation="eq:harmonic_mean">
+<!-- <div class="equation" align="center" data-raw-text="\begin{align}H &amp;= \frac{n}{\frac{1}{x_0} + \frac{1}{x_1} + \cdots + \frac{1}{x_{n-1}}} \\ &amp;= \frac{n}{\sum_{i=0}^{n-1} \frac{1}{x_i}} \\ &amp;= \biggl( \frac{\displaystyle \sum_{i=0}^{n-1} \frac{1}{x_i}}{n} \biggr)^{-1}\end{align}" data-equation="eq:harmonic_mean">
     <img src="https://cdn.jsdelivr.net/gh/stdlib-js/stdlib@0a561712608b99b59d9243f7d478a2e2a019a130/lib/node_modules/@stdlib/stats/incr/mhmean/docs/img/equation_harmonic_mean.svg" alt="Equation for the harmonic mean.">
     <br>
 </div> -->

lib/node_modules/@stdlib/stats/incr/mpcorr/README.md

@@ -43,10 +43,10 @@ where the numerator is the [covariance][covariance] and the denominator is the p
 
 For a sample of size `W`, the [sample Pearson product-moment correlation coefficient][pearson-correlation] is defined as
 
-<!-- <equation class="equation" label="eq:sample_pearson_correlation_coefficient" align="center" raw="r = \frac{\sum_{i=0}^{n-1} (x_i - \bar{x})(y_i - \bar{y})}{\sqrt{\sum_{i=0}^{n-1} (x_i - \bar{x})^2} \sqrt{\sum_{i=0}^{n-1} (y_i - \bar{y})^2}}" alt="Equation for the sample Pearson product-moment correlation coefficient."> -->
+<!-- <equation class="equation" label="eq:sample_pearson_correlation_coefficient" align="center" raw="r = \frac{\displaystyle\sum_{i=0}^{n-1} (x_i - \bar{x})(y_i - \bar{y})}{\sqrt{\sum_{i=0}^{n-1} (x_i - \bar{x})^2} \sqrt{\sum_{i=0}^{n-1} (y_i - \bar{y})^2}}" alt="Equation for the sample Pearson product-moment correlation coefficient."> -->
 
 ```math
-r = \frac{\sum_{i=0}^{n-1} (x_i - \bar{x})(y_i - \bar{y})}{\sqrt{\sum_{i=0}^{n-1} (x_i - \bar{x})^2} \sqrt{\sum_{i=0}^{n-1} (y_i - \bar{y})^2}}
+r = \frac{\displaystyle\sum_{i=0}^{n-1} (x_i - \bar{x})(y_i - \bar{y})}{\sqrt{\sum_{i=0}^{n-1} (x_i - \bar{x})^2} \sqrt{\sum_{i=0}^{n-1} (y_i - \bar{y})^2}}
 ```
 
 <!-- <div class="equation" align="center" data-raw-text="r = \frac{\sum_{i=0}^{n-1} (x_i - \bar{x})(y_i - \bar{y})}{\sqrt{\sum_{i=0}^{n-1} (x_i - \bar{x})^2} \sqrt{\sum_{i=0}^{n-1} (y_i - \bar{y})^2}}" data-equation="eq:sample_pearson_correlation_coefficient">

lib/node_modules/@stdlib/stats/incr/pcorr/README.md

@@ -43,13 +43,13 @@ where the numerator is the [covariance][covariance] and the denominator is the p
 
 For a sample of size `n`, the [sample Pearson product-moment correlation coefficient][pearson-correlation] is defined as
 
-<!-- <equation class="equation" label="eq:sample_pearson_correlation_coefficient" align="center" raw="r = \frac{\sum_{i=0}^{n-1} (x_i - \bar{x})(y_i - \bar{y})}{\sqrt{\sum_{i=0}^{n-1} (x_i - \bar{x})^2} \sqrt{\sum_{i=0}^{n-1} (y_i - \bar{y})^2}}" alt="Equation for the sample Pearson product-moment correlation coefficient."> -->
+<!-- <equation class="equation" label="eq:sample_pearson_correlation_coefficient" align="center" raw="r = \frac{\displaystyle\sum_{i=0}^{n-1} (x_i - \bar{x})(y_i - \bar{y})}{\displaystyle\sqrt{\sum_{i=0}^{n-1} (x_i - \bar{x})^2} \sqrt{\sum_{i=0}^{n-1} (y_i - \bar{y})^2}}" alt="Equation for the sample Pearson product-moment correlation coefficient."> -->
 
 ```math
-r = \frac{\sum_{i=0}^{n-1} (x_i - \bar{x})(y_i - \bar{y})}{\sqrt{\sum_{i=0}^{n-1} (x_i - \bar{x})^2} \sqrt{\sum_{i=0}^{n-1} (y_i - \bar{y})^2}}
+r = \frac{\displaystyle\sum_{i=0}^{n-1} (x_i - \bar{x})(y_i - \bar{y})}{\displaystyle\sqrt{\sum_{i=0}^{n-1} (x_i - \bar{x})^2} \sqrt{\sum_{i=0}^{n-1} (y_i - \bar{y})^2}}
 ```
 
-<!-- <div class="equation" align="center" data-raw-text="r = \frac{\sum_{i=0}^{n-1} (x_i - \bar{x})(y_i - \bar{y})}{\sqrt{\sum_{i=0}^{n-1} (x_i - \bar{x})^2} \sqrt{\sum_{i=0}^{n-1} (y_i - \bar{y})^2}}" data-equation="eq:sample_pearson_correlation_coefficient">
+<!-- <div class="equation" align="center" data-raw-text="r = \frac{\displaystyle\sum_{i=0}^{n-1} (x_i - \bar{x})(y_i - \bar{y})}{\displaystyle\sqrt{\sum_{i=0}^{n-1} (x_i - \bar{x})^2} \sqrt{\sum_{i=0}^{n-1} (y_i - \bar{y})^2}}" data-equation="eq:sample_pearson_correlation_coefficient">
     <img src="https://cdn.jsdelivr.net/gh/stdlib-js/stdlib@49d8cabda84033d55d7b8069f19ee3dd8b8d1496/lib/node_modules/@stdlib/stats/incr/pcorr/docs/img/equation_sample_pearson_correlation_coefficient.svg" alt="Equation for the sample Pearson product-moment correlation coefficient.">
     <br>
 </div> -->

lib/node_modules/@stdlib/stats/incr/pcorr2/README.md

@@ -43,13 +43,13 @@ where the numerator is the [covariance][covariance] and the denominator is the p
 
 For a sample of size `n`, the sample [Pearson product-moment correlation coefficient][pearson-correlation] is defined as
 
-<!-- <equation class="equation" label="eq:sample_pearson_correlation_coefficient" align="center" raw="r = \frac{\sum_{i=0}^{n-1} (x_i - \bar{x})(y_i - \bar{y})}{\sqrt{\sum_{i=0}^{n-1} (x_i - \bar{x})^2} \sqrt{\sum_{i=0}^{n-1} (y_i - \bar{y})^2}}" alt="Equation for the sample Pearson product-moment correlation coefficient."> -->
+<!-- <equation class="equation" label="eq:sample_pearson_correlation_coefficient" align="center" raw="r = \frac{\displaystyle\sum_{i=0}^{n-1} (x_i - \bar{x})(y_i - \bar{y})}{\displaystyle\sqrt{\sum_{i=0}^{n-1} (x_i - \bar{x})^2} \sqrt{\sum_{i=0}^{n-1} (y_i - \bar{y})^2}}" alt="Equation for the sample Pearson product-moment correlation coefficient."> -->
 
 ```math
-r = \frac{\sum_{i=0}^{n-1} (x_i - \bar{x})(y_i - \bar{y})}{\sqrt{\sum_{i=0}^{n-1} (x_i - \bar{x})^2} \sqrt{\sum_{i=0}^{n-1} (y_i - \bar{y})^2}}
+r = \frac{\displaystyle\sum_{i=0}^{n-1} (x_i - \bar{x})(y_i - \bar{y})}{\displaystyle\sqrt{\sum_{i=0}^{n-1} (x_i - \bar{x})^2} \sqrt{\sum_{i=0}^{n-1} (y_i - \bar{y})^2}}
 ```
 
-<!-- <div class="equation" align="center" data-raw-text="r = \frac{\sum_{i=0}^{n-1} (x_i - \bar{x})(y_i - \bar{y})}{\sqrt{\sum_{i=0}^{n-1} (x_i - \bar{x})^2} \sqrt{\sum_{i=0}^{n-1} (y_i - \bar{y})^2}}" data-equation="eq:sample_pearson_correlation_coefficient">
+<!-- <div class="equation" align="center" data-raw-text="r = \frac{\displaystyle\sum_{i=0}^{n-1} (x_i - \bar{x})(y_i - \bar{y})}{\displaystyle\sqrt{\sum_{i=0}^{n-1} (x_i - \bar{x})^2} \sqrt{\sum_{i=0}^{n-1} (y_i - \bar{y})^2}}" data-equation="eq:sample_pearson_correlation_coefficient">
     <img src="https://cdn.jsdelivr.net/gh/stdlib-js/stdlib@0086d9dadd17859fedeb3c5acc3a80d7011970e1/lib/node_modules/@stdlib/stats/incr/pcorr2/docs/img/equation_sample_pearson_correlation_coefficient.svg" alt="Equation for the sample Pearson product-moment correlation coefficient.">
     <br>
 </div> -->