Coursera R programming week2 notes2

2021/06/19 SAT

y <-10
f <- function(x){
    y <- 2
    y^2 + g(x)
}
g <- function(x) {
    x*y
}
f(3)

[1] 34

This shows the difference between Lexical Scoping and Dynamic Scopping.

Consequences of Lexical Scoping 1) In R, all objects must be stored in memory. 2) All functions must carry a pointer to their respective defining environments, which could be anywhere. 3) In S-PLUS, free variables are always looked up in the global workspace, so everything can be stored on the disk because the “defining environment” of all functions is the same.

Maximizing a Normal Likelihood

make.NegLogLik <- function(data, fixed = c(FALSE, FALSE)){
        params <- fixed
        function(p){
              params[!fixed] <- p
              mu <- params[1]
              sigma <- params[2]
              a <- -0.5*length(data)*log(2*pi*sigma^2)
              b <- -0.5*sum((data-mu)^2 / (sigma^2))
              -(a+b)
        }
}
set.seed(1); normals <- rnorm(100, 1, 2)
nLL <- make.NegLogLik(normals)
View(nLL)
ls(environment(nLL))

[1] "data"   "fixed"  "params"

看不懂，真不知道在讲啥 TAT mark 一下网址： https://www.coursera.org/learn/r-programming/lecture/Jm1s1/scoping-rules-optimization-example-optional

Coding Standards 1) Always use text files/ text editor 2) Indenting is IMPORTANT -> imporves readability Fixing line length(80 columns) prevents lots of nesting and vering long functions Suggested: Indents of 4 spaces at minimun; 8 spaces ideal

3)Limit

Dates and times 1) Date class 2) POSIXct or POSIXlt class 3) since 1970-01-01

x <- as.Date("1970-01-01")
x

[1] "1970-01-01"

unclass(x)

[1] 0

unclass(as.Date("1970-01-01"))

[1] 0

Current Time

Sys.time()

[1] "2021-06-19 10:35:37 CST"

p$sec

[1] 0

Use strptime function in case your dates are written in a different format

datestring <- c("January 10, 2012 10:40", "December 9, 2011 9:10")
x <- strptime(datestring, "%B %d, %Y %H:%M")
x

[1] "2012-01-10 10:40:00 CST" "2011-12-09 09:10:00 CST"

if you can not remember formatting strings

Operations on Dates and Times

y

[1] "2011-01-09 11:34:21 CST"

Showing the difference betwen x and y

x-y

Time difference of 356.8511 days

Different Time Zones

x <- as.Date("2012-03-01")
y <- as.Date("2012-02-28")
x- y

Time difference of 2 days

m <- as.POSIXct("2012-10-25 01:00:00")
n <- as.POSIXct("2012-10-25 06:00:00", tz = "GMT")
n - m

Time difference of 13 hours