View poisson reg.py
#-----------------------------------
# poisson regression basic example
#-----------------------------------
# see also: http://econometricsense.blogspot.com/2017/03/count-model-regressions.html
# this code is adapted from a more extensive GEE application
# set up to allow for repeated measures
http://nbviewer.jupyter.org/urls/umich.box.com/shared/static/ir0bnkup9rywmqd54zvm.ipynb
View python basic stats.py
#------------------------------------------------------------------
# PROGRAM NAME: python basic stats.py
# DATE: 2/20/16
# CREATED BY: MATT BOGARD
# PROJECT FILE:
#----------------------------------------------------------------
# PURPOSE: BASIC STATS IN PYTHON
#---------------------------------------------------------------
View R basic statistics.r
# ------------------------------------------------------------------
# |PROGRAM NAME: R basic statistics
# |DATE: 2/20/17
# |CREATED BY: MATT BOGARD
# |PROJECT FILE:
# |----------------------------------------------------------------
# | PURPOSE: BASIC STATISTICS IN R
# |----------------------------------------------------------------
# create some toy data
View python basic.py
#------------------------------------------------------------------
# PROGRAM NAME: Python Examples.py
# DATE: 6/1/16
# CREATED BY: MATT BOGARD
# PROJECT FILE:
#----------------------------------------------------------------
# PURPOSE: BASIC DATA MANAGEMENT AND STATS IN PYTHON
# ---------------------------------------------------------------
#---------------------------------
View rbasic.r
# ------------------------------------------------------------------
# |PROGRAM NAME: R basic data manipulation
# |DATE: 2/20/17
# |CREATED BY: MATT BOGARD
# |PROJECT FILE:
# |----------------------------------------------------------------
# | PURPOSE: BASIC DATA MANAGEMENT AND STATS IN R
# |----------------------------------------------------------------
# create some toy data
View rbasic.r
# ------------------------------------------------------------------
# |PROGRAM NAME: R basic data manipulation
# |DATE: 2/20/17
# |CREATED BY: MATT BOGARD
# |PROJECT FILE:
# |----------------------------------------------------------------
# | PURPOSE: BASIC DATA MANAGEMENT AND STATS IN R
# |----------------------------------------------------------------
View neuralnet.r
# ------------------------------------------------------------------
# |PROGRAM NAME: NEURALNET_PKG_R
# |DATE: 12/3/10
# |CREATED BY: MATT BOGARD
# |PROJECT FILE: http://econometricsense.blogspot.com/2010/12/r-code-example-for-neural-networks.html
# |----------------------------------------------------------------
# | PURPOSE: DEMO OF THE 'neuralnet' PACKAGE AND OUTPUT INTERPRETATION
# |
# | ADAPTED FROM: neuralnet: Training of Neural Networks
# | by Frauke Günther and Stefan Fritsch The R Journal Vol. 2/1, June 2010
View bubble crops.r
# -------------------------------------------------------------
# | PROGRAM NAME: Bubble_Crops
# | DATE: 12-4-2010
# | CREATED BY: Matt Bogard
# | PROJECT FILE: http://econometricsense.blogspot.com/2010/12/visualizing-agricultural-subsidies-by.html
# |-------------------------------------------------------------
# | PURPOSE: Intitially to create bubble charts to demonstrate
# | allocation
# | of farm subsides to producers by KY county, but expanded to
# | include
View google vis.r
# ------------------------------------------------------------------
# | PROGRAM NAME: googleVis_R
# | DATE: 1/12/11
# | CREATED BY: Matt Bogard
# | PROJECT FILE:http://econometricsense.blogspot.com/2011/01/r-code-for-googlevis-demo.html
# |----------------------------------------------------------------
# | PURPOSE: Tutorial for creating Motion Charts in R with the GoogleVis package
# |
# |
# |
View density plots.r
### r code to support: http://econometricsense.blogspot.com/2011/01/flexibility-of-r-graphics.html
library(colorspace) # package for rainbow_hcl function
ds <- rbind(data.frame(dat=KyCropsAndSubsidies[,][,"LogAcres"], grp="All"),
data.frame(dat=KyCropsAndSubsidies[,][KyCropsAndSubsidies$subsidy_in_millions > 2.76,"LogAcres"], grp=">median"),
data.frame(dat=KyCropsAndSubsidies[,][KyCropsAndSubsidies$subsidy_in_millions <= 2.76,"LogAcres"], grp="<=median"))