Enclosing Circle Algorithm - Revision history

Ed at 17:47, 21 September 2020

2020-09-21T17:47:35Z

Ed at 17:34, 21 September 2020

2020-09-21T17:34:30Z

Ed at 17:19, 20 September 2020

2020-09-20T17:19:58Z

Ed at 17:12, 20 September 2020

2020-09-20T17:12:11Z

MichelleH at 14:54, 31 October 2017

2017-10-31T14:54:36Z

MichelleH at 14:54, 31 October 2017

2017-10-31T14:54:04Z

KerdaV at 16:45, 20 June 2017

2017-06-20T16:45:56Z

KerdaV at 01:36, 20 June 2017

2017-06-20T01:36:37Z

KerdaV at 01:32, 20 June 2017

2017-06-20T01:32:44Z

AbhiB: /* Visualization */

2017-06-14T20:12:31Z

Visualization

@@ Line 1: / Line 1: @@
 {{Project
-|Has project output=
+|Has project output=Tool
 |Has sponsor=McNair Center
 |Has title=Enclosing Circle Algorithm

@@ Line 1: / Line 1: @@
 {{Project
 |Has sponsor=McNair Center
 |Has title=Enclosing Circle Algorithm

@@ Line 1: / Line 1: @@
 {{Project
 |Has title=Enclosing Circle Algorithm
 |Has owner=Christy Warden, Peter Jalbert,

@@ Line 1: / Line 1: @@
-{{McNair Projects
+{{Project
 |Has title=Enclosing Circle Algorithm
 |Has owner=Christy Warden, Peter Jalbert,

@@ Line 5: / Line 5: @@
 |Has deadline=April 2017
 |Has keywords=Tool
-|Has project status=Active
+|Has project status=Subsume
 |Has Image=Red-circle.jpg
 }}

← Older revision		Revision as of 16:45, 20 June 2017
Line 264:		Line 264:
	You can plot this data onto a map using the script located:		You can plot this data onto a map using the script located:
	E:\McNair\Projects\Accelerators\EnclosingCircle\Draw_circles_test\draw_vc_circles.py		E:\McNair\Projects\Accelerators\EnclosingCircle\Draw_circles_test\draw_vc_circles.py
−
−	~~=Summary=~~
−	Clusters of economic activity plays a significant role in the firms performance and growth. An important driver of growth is the knowledge spillover between firms. This includes among others the facilitation of information flow and ideas between firms which could be a milestone especially in the growth of startup firms or small businesses. This project focuses on the effects of agglomeration on the performance and growth of venture capital backed up firms. It introduces a novel measure of agglomeration which can be used to empirically test the effects of clustering. This measure the is smallest total circle area that covers all of the startups in the sample such that there are at least n firms in each circle. The projects is based on the creation of an algorithm which gives an unbiased measure to be used in the empirical analysis. The regression we are interested in takes the following form:
−
−	~~[[File:regression_equation.png]]~~
−
−	The dependent variable is a measure of growth of the firms. This measure could be investment forwarded one period or growth in investment. The control variables include the number of the startups firms, m, the agglomeration measure, A and a vector of other control variables affecting the growth of firms at time t. Because of the endogeneity in the circle area or the measure of agglomeration, A, there is a need for an instrumental variable to get consistent estimates of the effects we are interested in. The proposed instrument is the presence of a river, or road in between the points representing geographical locations of the venture capital backed up firms. The instrument affects the total circle area without having a direct impact on the growth. This makes it good candidate for a valid instrument.
−	~~The next tasks are determining the additional control variables to include in the regression, years to include in the analysis and methods of finding an unbiased measure of agglomeration.~~

@@ Line 265: / Line 265: @@
   E:\McNair\Projects\Accelerators\EnclosingCircle\Draw_circles_test\draw_vc_circles.py
-===Summary===
+=Summary=
 Clusters of economic activity plays a significant role in the firms performance and growth. An important driver of growth is the knowledge spillover between firms. This includes among others the facilitation of information flow and ideas between firms which could be a milestone especially in the growth of startup firms or small businesses. This project focuses on the effects of agglomeration on the performance and growth of venture capital backed up firms. It introduces a novel measure of agglomeration which can be used to empirically test the effects of clustering. This measure the is smallest total circle area that covers all of the startups in the sample such that there are at least n firms in each circle. The projects is based on the creation of an algorithm which gives an unbiased measure to be used in the empirical analysis.  The regression  we are interested in takes the following form:

← Older revision		Revision as of 01:32, 20 June 2017
Line 264:		Line 264:
	You can plot this data onto a map using the script located:		You can plot this data onto a map using the script located:
	E:\McNair\Projects\Accelerators\EnclosingCircle\Draw_circles_test\draw_vc_circles.py		E:\McNair\Projects\Accelerators\EnclosingCircle\Draw_circles_test\draw_vc_circles.py
		+
		+	===Summary===
		+	Clusters of economic activity plays a significant role in the firms performance and growth. An important driver of growth is the knowledge spillover between firms. This includes among others the facilitation of information flow and ideas between firms which could be a milestone especially in the growth of startup firms or small businesses. This project focuses on the effects of agglomeration on the performance and growth of venture capital backed up firms. It introduces a novel measure of agglomeration which can be used to empirically test the effects of clustering. This measure the is smallest total circle area that covers all of the startups in the sample such that there are at least n firms in each circle. The projects is based on the creation of an algorithm which gives an unbiased measure to be used in the empirical analysis. The regression we are interested in takes the following form:
		+
		+	[[File:regression_equation.png]]
		+
		+	The dependent variable is a measure of growth of the firms. This measure could be investment forwarded one period or growth in investment. The control variables include the number of the startups firms, m, the agglomeration measure, A and a vector of other control variables affecting the growth of firms at time t. Because of the endogeneity in the circle area or the measure of agglomeration, A, there is a need for an instrumental variable to get consistent estimates of the effects we are interested in. The proposed instrument is the presence of a river, or road in between the points representing geographical locations of the venture capital backed up firms. The instrument affects the total circle area without having a direct impact on the growth. This makes it good candidate for a valid instrument.
		+	The next tasks are determining the additional control variables to include in the regression, years to include in the analysis and methods of finding an unbiased measure of agglomeration.

@@ Line 102: / Line 102: @@
 ==Visualization ==
 The K-Means based algorithm returns the optimal solution, albeit slower <br>
-[[File:kmeans comparison.png]]
+[[File:kmeans comparison.png]] [[File:kmeans random.png]] [[File:houston.png]]
 =Brute Force=