docs: improve examples of stats/base/dists/exponential namespace

lib/node_modules/@stdlib/stats/base/dists/exponential/README.md

@@ -107,14 +107,247 @@ var y = dist.logpdf( 0.8 );
 <!-- TODO: better examples -->
 
 <!-- eslint no-undef: "error" -->
-
+### Object Keys
 ```javascript
 var objectKeys = require( '@stdlib/utils/keys' );
 var exponential = require( '@stdlib/stats/base/dists/exponential' );
 
 console.log( objectKeys( exponential ) );
 ```
+### Cumulative Distribution Function (CDF)
+```javascript
+var exponential = require('@stdlib/stats/base/dists/exponential');
+```
+#### cdf(x, lambda)
+
+Evaluates the [cumulative distribution function][cdf] of an exponential distribution with rate parameter `lambda`.
+
+```javascript
+var y = cdf(1.0, 2.0);
+// returns ~0.864
+
+y = cdf(0.5, 1.0);
+// returns ~0.393
+
+y = cdf(-1.0, 4.0);
+// returns 0.0
+```
+#### cdf.factory(lambda)
+
+Returns a function for evaluating the [cumulative distribution function][cdf] of an exponential distribution with rate parameter `lambda`.
+
+```javascript
+var mycdf = cdf.factory(2.0);
+
+var y = mycdf(1.0);
+// returns ~0.864
+
+y = mycdf(0.3);
+// returns ~0.451
+```
+### Logarithm of the Cumulative Distribution Function (logCDF)
+```javascript
+var logcdf = require('@stdlib/stats/base/dists/exponential/logcdf');
+```
+#### logcdf(x, lambda)
+Evaluates the natural logarithm of the cumulative distribution function for an exponential distribution with rate parameter `lambda`.
+
+```javascript
+var y = logcdf(1.0, 2.0);
+// returns ~-0.146
+
+y = logcdf(0.5, 1.0);
+// returns ~-0.934
+
+y = logcdf(-1.0, 4.0);
+// returns -Infinity
+```
+#### logcdf.factory(lambda)
+Returns a function for evaluating the natural logarithm of the cumulative distribution function for an exponential distribution with rate parameter `lambda`.
+
+```javascript
+var mylogcdf = logcdf.factory(2.0);
 
+var y = mylogcdf(1.0);
+// returns ~-0.146
+
+y = mylogcdf(0.3);
+// returns ~-0.797
+```
+### Probability Density Function(PDF)
+```javascript
+var pdf = require('@stdlib/stats/base/dists/exponential/pdf');
+```
+
+#### pdf(x, lambda)
+Evaluates the [probability density function][pdf] of an exponential distribution with rate parameter `lambda`.
+
+```javascript
+var y = pdf(1.0, 2.0);
+// returns ~0.271
+
+y = pdf(0.5, 1.0);
+// returns ~0.607
+
+y = pdf(-1.0, 4.0);
+// returns 0.0
+```
+#### pdf.factory(lambda)
+Returns a function for evaluating the [probability density function][pdf] of an exponential distribution with rate parameter `lambda`.
+```javascript
+var mypdf = pdf.factory(2.0);
+
+var y = mypdf(1.0);
+// returns ~0.271
+
+y = mypdf(0.3);
+// returns ~0.74
+```
+### Logarithm of the Probability Density Function (logPDF)
+```javascript
+var logpdf = require('@stdlib/stats/base/dists/exponential/logpdf');
+```
+#### logpdf(x, lambda)
+Evaluates the natural logarithm of the probability density function for an exponential distribution with rate parameter `lambda`.
+
+```javascript
+var y = logpdf(1.0, 2.0);
+// returns ~-1.307
+
+y = logpdf(0.5, 1.0);
+// returns ~-0.5
+
+y = logpdf(-1.0, 4.0);
+// returns -Infinity
+```
+#### logpdf.factory(lambda)
+Returns a function for evaluating the natural logarithm of the probability density function for an exponential distribution with rate parameter `lambda`.
+
+```javascript
+var mylogpdf = logpdf.factory(2.0);
+
+var y = mylogpdf(1.0);
+// returns ~-1.307
+
+y = mylogpdf(0.3);
+// returns ~-0.599
+```
+### Quantile Function
+```javascript
+var quantile = require('@stdlib/stats/base/dists/exponential/quantile');
+```
+#### quantile(p, lambda)
+Evaluates the [quantile function][quantile-function] for an exponential distribution with rate parameter `lambda`.
+```javascript
+var y = quantile(0.8, 2.0);
+// returns ~0.916
+
+var y = quantile(0.5, 1.0);
+// returns ~0.693
+```
+#### quantile.factory(lambda)
+Returns a function for evaluating the [quantile function][quantile-function] of an exponential distribution with rate parameter `lambda`.
+```javascript
+var myQuantile = quantile.factory(2.0);
+
+var y = myQuantile(0.4);
+// returns ~0.511
+
+var y = myQuantile(1.0);
+// returns Infinity
+```
+### Moment-Generating Function (MGF)
+```javascript
+var mgf = require('@stdlib/stats/base/dists/exponential/mgf');
+```
+#### mgf(t, lambda)
+Evaluates the [moment-generating function][mgf] of an exponential distribution with rate parameter `lambda`.
+```javascript
+var y = mgf(1.0, 2.0);
+// returns ~1.5
+
+var y = mgf(0.5, 1.0);
+// returns ~2.0
+```
+#### quantile.factory(lambda)
+mgf.factory(lambda)
+Returns a function for evaluating the [moment-generating function][mgf] of an exponential distribution with rate parameter `lambda`.
+```javascript
+var mymgf = mgf.factory(2.0);
+
+var y = mymgf(1.0);
+// returns ~1.5
+
+var y = mymgf(0.3);
+// returns ~1.25
+```
+### Entropy(lambda)
+Evaluates the differential entropy of an exponential distribution with rate parameter `lambda`.
+```javascript
+var entropy = require('@stdlib/stats/base/dists/exponential/entropy');
+
+var y = entropy(2.0);
+// returns ~0.306
+```
+### Median(lambda)
+Evaluates the median of an exponential distribution with rate parameter `lambda`.
+```javascript
+var median = require('@stdlib/stats/base/dists/exponential/median');
+
+var y = median(2.0);
+// returns ~0.347
+```
+### Mode(lambda)
+Evaluates the mode of an exponential distribution with rate parameter `lambda`.
+```javascript
+var mode = require('@stdlib/stats/base/dists/exponential/mode');
+
+var y = mode(2.0);
+// returns 0.0
+```
+### Skewness(lambda)
+Evaluates the skewness of an exponential distribution with rate parameter `lambda`.
+```javascript
+var skewness = require('@stdlib/stats/base/dists/exponential/skewness');
+
+var y = skewness(2.0);
+// returns 2.0
+```
+### Standard Deviation(lambda)
+Evaluates the standard deviation of an exponential distribution with rate parameter `lambda`.
+```javascript
+var stdev = require('@stdlib/stats/base/dists/exponential/stdev');
+
+var y = stdev(2.0);
+// returns 0.5
+```
+### Variance(lambda)
+Evaluates the variance of an exponential distribution with rate parameter `lambda`.
+```javascript
+var variance = require('@stdlib/stats/base/dists/exponential/variance');
+
+var y = variance(2.0);
+// returns 0.25
+```
+### Using the Constructor
+#### Creating an Exponential Distribution Object
+```javascript
+var Exponential = require('@stdlib/stats/base/dists/exponential').Exponential;
+
+var dist = new Exponential(2.0);
+
+var y = dist.pdf(0.8);
+// returns ~0.271
+```
+#### Using Distribution Object Methods
+Evaluate the mean and variance using the distribution object:
+```javascript
+console.log('Mean: ' + dist.mean);
+// Output: Mean: 0.5
+
+console.log('Variance: ' + dist.variance);
+// Output: Variance: 0.25
+```
 </section>
 
 <!-- /.examples -->