MacKay Minutes 2016/07/7

MacKay website, and minutes

How did we do on our todo list?

File:DataOrganizationReports.pdf This is a pdf. I'm not sure how to change it to a CSV file.

• We could use some help shoring up the historical in our paper: the introduction (summary of the 1901 paper), and a look back over some of the others (e.g. 1910, to explain what caused a loss of the data for that year).
  • Historical predecessor to MacKay?
    • https://archive.org/details/cbarchive_51490_1891phenologyandruralbiologyth9999
    • https://archive.org/stream/cbarchive_51490_1891phenologyandruralbiologyth9999/1891phenologyandruralbiologyth9999_djvu.txt
    • Such observations would be useful in exciting an interest in natural science among the young, as they would form matter for recording the birthdays of flowers, butterflies, and birds, and with which children may compare their own birthdays and those of their friends* For natural history classes in schools it will supply lists of objects to be sought for on country walks and excursions at the proper seasons, and it will furnish special and appropriate subjects for teachers and lectures to explain at the proper seasons,

• Andy
  • will produce first regressions for FAT versus Soil Temperature
    • Interesting, but not exactly what I'd expected....
    • Interesting, but not exactly what I'd expected....
      • some of the raw results
      • some of the raw results
      • and comparison with AT
  • put FAT model stuff done so far into R
    • got started on this, but haven't made any significant progress.
  • will check out R code provided by Steve, to see what's different between our imputeSVD and imputePCA
    • The first thing I did was try to see if I could reproduce our results using the options from imputePCA
    • http://mathstat.nku.edu/rstudio/, sourcing file /home/longa/mackay/R/yarmouth/imputePCA.R
    • Did I see optional arguments in that Mathematica code?:)

• Laura
  • Will produce graphics of the "factors" of the rank-two approximation
    • Mathematica file with graphics
    • missed something above....
  • Will try the rank-three regressions
  • Will try to incorporate the results into wiki tables

ftp://longa@norsemathology.org@ftp.norsemathology.org/laura/SVDCoefficients.nb http://www.norsemathology.org/laura/SVDCoefficients.nb

• Madison
  • Will try to get soil reports for Nova Scotia (broadly); Dalhousie University might have some info for us....
    • http://sis.agr.gc.ca/cansis/publications/surveys/ns/index.html
    • http://sis.agr.gc.ca/cansis/nsdb/dss/v3/index.html
  • Will flesh out the intro historical stuff (1901 and perhaps discuss 1910 situation)
  • Will scan an image or two out of Tufte, and add to the report (as well as a reference in the bibliography).
    • File:SmallMultiplesTufte.pdf
    • File:SmallMultiplesTufte2.pdf
    • File:TimeSeriesTufte.pdf
    • File:TimeSeriesTufte2.pdf
    • File:Statistical analysis Tufte.pdf
    • File:TufteStatPic.pdf
  • Will get us a new Recipe of the Week
    • http://www.wholefoodsmarket.com/recipe/lentil-chili Half this recipe! It makes a lot.

• Steve
  • will get us his new Mathematica code for imputation, and examples
    • Code that allows imputation with specified rank. All could use some more testing. The Mathematica and python code are a little more flexible and better commented than the R code. The added flexibility is that the variable values can either be interpreted as the rows or as the columns in Mathematica and python. Whereas in R they are in columns only. Also, in Mathematica and python, the initial guesses can be computed as either the mean of all the values for the variable or just the nearest values. Whereas in R the initial guesses are the mean of all the values of the variable. There is no option to use just the nearest values.
      • Mathematica code: <http://www.nku.edu/~wilkinson/research/2016summer/mackay/ImputeMSVv3.0.nb>
      • R code: <http://www.nku.edu/~wilkinson/research/2016summer/mackay/ImputeMSV.R>
      • Python code: <http://www.nku.edu/~wilkinson/research/2016summer/mackay/MissingData.py>

• • will make available code for imputePCA R code.

The Readings

Why don't we try to get caught up to the Charney report for a discussion next week of climate change?

Moving forward

• Climate and first appearance: what is our model?
  • Do atmospheric temp and precipitation constitute "climate"? How about ocean currents?
  • Soil temperature as a function of climate -- we've got a model to start with (Chang, et al.).
  • One of our "In the News" items suggests the importance of light (even artificial light).
• Can we use the rank one version of our five favorite species, to reduce noise? We create one new variable from the top five, and follow it through time and space....
  • Now Laura is trying the rank-two versions.

In the News

• For Madison: What a fruit fly’s body temperature could reveal about climate change: A Canadian study shows insects’ response to temperature could help scientists understand how climate change will affect where animals live.

Todo for next week

• Andy

• Laura

• Madison
  • Still recovering from the bachelorette party....

• Steve
  • will be in Japan. He is charge of saki consumption....:)

Next meeting

Thursday, 7/7, noon

Steve will be out for the rest of the Month after that; Andy may not be available on the 14th (although I should be able to get free for an hour -- the question in my mind is simply what I can do). Maybe we could talk about climate change for an hour or so -- basic theory. Some of the mathematics.