updated notes/comments

Census2022-CER-calculate-AR.do

@@ -8,6 +8,8 @@
 * Calculate the AR coefficients for mid-weeks (Tues-Thurs) and weekends to 
 * add to the regression modelling approach to estimating household characteristics
 
+* For the latest version of this code go to: https://github.com/dataknut/Census2022
+
 * This work was funded by RCUK through the ESRC's Transformative Social Science Programme via the
 * "Census 2022: Transforming Small Area Socio-Economic Indicators through 'Big Data'" Project 
 * - http://gtr.rcuk.ac.uk/project/2D2CD798-4F04-4399-B1AF-D810A233DD21

Census2022-CER-data-exploration.do

@@ -8,7 +8,9 @@
 * "Census 2022: Transforming Small Area Socio-Economic Indicators through 'Big Data'" Project 
 * - http://gtr.rcuk.ac.uk/project/2D2CD798-4F04-4399-B1AF-D810A233DD21
 * - http://www.energy.soton.ac.uk/tag/census2022/
- 
+
+## For the latest version of this code go to: https://github.com/dataknut/Census2022
+
 Copyright (C) 2014  University of Southampton
 
 Author: Ben Anderson (b.anderson@soton.ac.uk, @dataknut, https://github.com/dataknut) 
@@ -81,6 +83,7 @@ su ba_floorarea, de
 tab ba_income, mi
 
 * switch to the daily summaries
+* this includes Sharon's weekend & midweek cluster membership variables
 use "$pdfiles/Oct-2009-daily-summaries-survey-$version.dta", clear
 
 di "* check collinearity 'As a rule of thumb, a tolerance of 0.1 or less (equivalently VIF of 10 or greater)  is a cause for concern. '"

Census2022-CER-data-processing.do

@@ -6,6 +6,8 @@
 
 * Processes & merges various files (mostly) created by Census2022 project team
 
+## For the latest version of this code go to: https://github.com/dataknut/Census2022
+
 * This work was funded by RCUK through the ESRC's Transformative Social Science Programme via the
 * "Census 2022: Transforming Small Area Socio-Economic Indicators through 'Big Data'" Project 
 * - http://gtr.rcuk.ac.uk/project/2D2CD798-4F04-4399-B1AF-D810A233DD21

Census2022-Lboro1min-consumption-by-hh-category-March-2008-graphs.do

@@ -8,6 +8,8 @@
 * by whatever category you set up (or all of them)
 * use medians through-out
 
+## For the latest version of this code go to: https://github.com/dataknut/Census2022
+
 * This work was funded by RCUK through the ESRC's Transformative Social Science Programme via the
 * "Census 2022: Transforming Small Area Socio-Economic Indicators through 'Big Data'" Project 
 * - http://gtr.rcuk.ac.uk/project/2D2CD798-4F04-4399-B1AF-D810A233DD21

Census2022-Lboro1min-consumption-by-hh-category-March-2008-models.do

@@ -6,6 +6,8 @@
 * - Comparing energy demand profiles for different kinds of households
 * Loops over March data producing regression models
 
+## For the latest version of this code go to: https://github.com/dataknut/Census2022
+
 * This work was funded by RCUK through the ESRC's Transformative Social Science Programme via the
 * "Census 2022: Transforming Small Area Socio-Economic Indicators through 'Big Data'" Project 
 * - http://gtr.rcuk.ac.uk/project/2D2CD798-4F04-4399-B1AF-D810A233DD21