Demos examples standalone nodejs and angular

README.md

@@ -18,6 +18,12 @@ const regression = d3.regressionLinear()
 </script>
 ```
 
+
+## Demos 
+- [Angular](https://stackblitz.com/edit/angular-ivy-dksajy?file=src/app/app.component.ts)
+
+- [Standalone NodeJS](/examples/linear.js)
+
 ## API Reference
 - [Linear](#regressionLinear)
 - [Exponential](#regressionExp)
@@ -229,4 +235,4 @@ See [<em>linear</em>.y()](#linear_y).
 
 <a name="loess_bandwidth" href="#loess_bandwidth">#</a> <i>loess</i>.<b>bandwidth</b>([<i>bandwidth</i>]) · [Source](https://github.com/harrystevens/d3-regression/blob/master/src/loess.js#L77 "Source")
 
-If <em>bandwidth</em> is specified, sets the LOESS regression's bandwidth, or smoothing parameter, to the specific number between 0 and 1. The bandwidth represents the share of the total data points that are used to calculate each local fit. Higher bandwidths produce smoother lines, and vice versa. If <em>bandwidth</em> is not specified, returns a copy of the regression generator’s current bandwidth, which defaults to .3.
+If <em>bandwidth</em> is specified, sets the LOESS regression's bandwidth, or smoothing parameter, to the specific number between 0 and 1. The bandwidth represents the share of the total data points that are used to calculate each local fit. Higher bandwidths produce smoother lines, and vice versa. If <em>bandwidth</em> is not specified, returns a copy of the regression generator’s current bandwidth, which defaults to .3.

examples/linear.js

@@ -0,0 +1,33 @@
+
+// Run with node linear.js
+var d3 = require('d3-regression');
+
+data2 = [{ x: 8, y: 3 }, { x: 2, y: 10 }, { x: 11, y: 3 }, { x: 6, y: 6 }, { x: 5, y: 8 }, { x: 4, y: 12 }, { x: 12, y: 1 }, { x: 9, y: 4 }, { x: 6, y: 9 }, { x: 1, y: 14 }]
+
+data3 = [{ x: 0, y: 1 },  { x: 1, y: 2 }, { x: 2, y: 3 }]
+
+data =  [
+      { x: 0, y: 3.3 },
+      { x: 1, y: 3.5 },
+      { x: 2, y: 3.8 },
+      { x: 3, y: 4.1 },
+      { x: 4, y: 4.4 },
+      { x: 5, y: 4.7 },
+      { x: 6, y: 4.9 },
+      { x: 7, y: 5.2 },
+      { x: 8, y: 5.4 },
+      { x: 9, y: 5.6 }
+    ]
+
+
+linearRegression = d3.regressionLinear()
+  .x(d => d.x)
+  .y(d => d.y)
+  .domain([-1.7, 16]);
+
+// Select your data sourse
+const regressionLine = linearRegression(data3);
+
+console.log(regressionLine);
+
+console.log(regressionLine.predict(1));