Thanks. I was unable to view the json easily so had not dug any deeper. Do you know where the electoral commission normally publishes their data? I was trying to find 2015 to no avail.
As a developer of this product, I wanted to mention that we highly discourage people from detecting change from this product. A much simpler and more straightforward change detection approach could have been done directly on the MODIS surface reflectance data to get a better estimate of land use change. Please contact me if you have any questions.
Hey, I think this is a very good attempt to try on this issue! My train got delayed for nearly 2 hours in the evening and I nearly miss the vote. Weather alone may not directly affect the vote… However, if you lay out other disruptions such as train delays and traffic congestion that are affected by weather, you will get a more convincing result. Keep up the good work!
I think what is missing is a comparison to at least one other national election where weather varied across the country. That way, you could potentially control for the demographic differences inherent in cross- regional comparisons.
I found that I wasn’t able to upload files directly to the shiny-server directory on AWS. I first needed to upload them to home/ubuntu and then move them to the srv/shiny-server directory because of the permissions granted to the ubuntu login. I encountered this with both PuTTY and WinSCP.
I also found it helpful to restart the shiny-server after changing the port settings on the AWS instance.
Quick question (without looking at your code): how do you define a raster cell as “non-land”? Usual problem is that if you intersect with a highres polygon, you’re in trouble with defining how much land is needed to define it as “land”.
This is especially relevant for islands.
I hit a wall with the gBuffer step: m2 = gBuffer(m, id=m$id) results in error: “if applying across ids, new id must be length 1″. This is confusing as it seems contradictory with the whole point of the id argument.
I’m impressed by your blog quality. I have two specific questions: how did you get all these house prices through Zillow, and how did you find the geo coordinates of these addresses? I was under the impression that finding the geolocation of 100 000 addresses was hard.
Just a short comment on the efficiency of multi-threading in felm(). It depends on two things.
Not everything is multi-threaded, only the centring of the covariates. The creation of a model matrix from the data frame is not, and often takes a substantial amount of time. The longer it takes to centre the covariates, the more there is to gain from multi-threading. (Because the non-threaded stuff then takes a smaller fraction of the time).
The other factor influencing parallel efficiency is the memory speed. Centring the covariates is a computationally simple process; i.e. little work is done on every observation of the dataset. Since a typical CPU runs quite much faster than it’s possible to fetch data from memory, the computation easily becomes limited by the time it takes to access memory, not by the computation speed (clock frequency) of the CPU. The problem gets worse when more parallel threads fetch data from memory simultaneously.
du erähnst eine Vermutung (“beim GRE zählt wohl allein der Matheteil”) in deinem obrigen Post. Kannst du diese mittlerweile bestätigen?
Bin auch sehr an einem Stuium in England interessiert, das Problem ist meines Erachtens nur die verbal-section beim GRE, da diese für einen Ausländer doch nur sehr schwierig zu schaffen ist.
Vielen Dank für deine Antwort im Voraus.
Thank you, that wasreally interesting. Actually,I was born in Moscow in 1974 but my mother and I fled the country and settled here to Britain. Honestly, I didnt really care much about my russian history until my mother died recently, now I’ve been trying to find out as much as I possibly can. Seemed like food was as good a place as any to start from! You dont generally hear much about russian cooking do you? Anyway, I found a lot of russian recipes here that your readers might be interested in .
Hallo! Hier noch ein Anhänger der Behavioural – oder, for lack of a better word: menschlicheren – Economics. Kontempliere einen PhD, in England. Auf Deine Seite bin ich beim Suchen danach gestoßen. Wie ist Deine Erfahrung, empfiehlst Du LSE? UCL scheint mit dem ELSE dafür auch ein gutes Umfeld zu bieten. Nottingham? Ich bin unentschlossen, wäre dankbar für Tips!
Du schreibst in dem Thread auch, Du hättest Dich in Oxford beworben. Bis wann hast Du von dort eine Rückmeldung erhalten? Bereits kurz nach Mitte März oder zum späteren Zeitpunkt, wenn die Colleges entscheiden mussten?