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Introduction

UT的R語言，比起上次的A1，這次的竟然要求畫56張圖，真是喪心病狂。
使用Data frames去讀取數(shù)據(jù)，然后運(yùn)算，然后寫函數(shù)去運(yùn)算，不能使用index而只能慢慢的去loop，效率低不說，這么大的數(shù)據(jù)量，卡是必然的。
每個(gè)圖差不多都要運(yùn)行5秒才能得出結(jié)果，畫全套圖得好幾分鐘才能完成。

Requirement

You should write R scripts for predicting future values of a time sequence in this assignment, and use them to observations on numbers of maximum temperatures and deaths.
The datasets is derived from that distributed by the NMMAPS, the U.S. National Morbidity Mortality Air Pollution Study, with some missing temperature values. I have provided the datasets from 2000-12-31 to 1994-01-01 as a csv file on the course web page.
Finishing this assignment should provide more practice in basic R scripts, and on the knowledge of datasets frames and of subscripts that are logical or numeric lists.
We wish to predict the number of the maximum temperature and deaths for every day, based only on datasets before that day, except that when predicting the number of deaths on a day, we may use the maximum temperature for that day, as well as previous days.
You should also write a function called predictions, which makes predicts for all days from some start point to the last day for which datasets is provided. This function should take as its arguments a function to use for predicting, a datasets frame with values that may be used for predicting, the series of values for which predicts are to be made, and the start point for making predicts of this series. It should return a list of predicts for values in the series from the specified start point to the end.
Once you have produced predicts for every day, you should produce plots of the predicts, the actual values, and the errors in the predicts. You should also evaluate how good these predicts were in terms of the average absolute value of the error.
You should write several functions for predicting the value of some variable on a single day. All these functions should take as their first arguments a datasets frame, containing variables that may be used in making the predict, and as their second argument a series of past values for the variable being predict (which should have at least one past value, and for some functions should have to have more than one past value). This predicting function should return a predict for the next value in this series. The datasets frame should have at least as many rows as the length of the series plus one (so there should be values for the day for which the predict is being made). The datasets frame may have additional rows, but they should not be looked at when making the predict for this day.
Finally, you should try a more powerful predicting method, in which you first make predicts with some function, and then try to use another function to predict the error in the first method. The idea is that if you can manage to predict the error well, you can get a better predict by just adding the predicted error to the original prediction.

Summary

這次作業(yè)竟然寫了快400行代碼，畫了56張圖，完全就是個(gè)體力活。