Displaying 6 results from an estimated 6 matches for "yfit1".
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fit1
2010 Jan 18
5
errors appears in my time Series regression fomula
....txt',skip=2,nlines=18)
Read 144 items
> yts=ts(log(y))
> plot(yts,main="LOG AIRLINE TOTALS",type='p',col=2)
> n=length(y)
> time=seq(1:n)
>
> month=c(rep(seq(1:12),12))
> fmonth=as.factor(month)
> ymod1=lm(yts~time+fmonth)
> summary(ymod1)
> yfit1=ymod1$fitted
> lines(yfit1,c=3)
??? plot.xy(xy.coords(x, y), type = type, ...) :
??3?????????????
Also, for a similar data set quarterly sales of spirits series, what is the best model to use?? Should I use ARIMA??
Many thanks and regard,
Cathy Wong
_________________...
2007 Aug 23
0
weighted nls and confidence intervals
...0.05
x <- 1:10
y <- rnorm(x, x, .8)
w1 <- rep(1, 10)
w2 <- w1; w2[7:10] <- 0.01 * w2[7:10]
rr1 <- nls(y ~ a*x + b, data = list(x = x, y = y), start = list(a = 1, b = 0), weights = w1)
rr2 <- nls(y ~ a*x + b, data = list(x = x, y = y), start = list(a = 1, b = 0), weights = w2)
yfit1 <- fitted(rr1)
yfit2 <- fitted(rr2)
se.fit1 <- sqrt(apply(rr1$m$gradient(), 1, function(x) sum(vcov(rr1)*outer(x,x))))
luconf1 <- yfit1 + outer(se.fit1, qnorm(c(probex, 1 - probex)))
se.fit2 <- sqrt(apply(rr2$m$gradient(), 1, function(x) sum(vcov(rr2)*outer(x,x))))
luconf2 <- yfi...
2007 Aug 31
0
non-linear fitting (nls) and confidence limits
...0.05
x <- 1:10
y <- rnorm(x, x, .8)
w1 <- rep(1, 10)
w2 <- w1; w2[7:10] <- 0.01 * w2[7:10]
rr1 <- nls(y ~ a*x + b, data = list(x = x, y = y), start = list(a = 1, b = 0), weights = w1)
rr2 <- nls(y ~ a*x + b, data = list(x = x, y = y), start = list(a = 1, b = 0), weights = w2)
yfit1 <- fitted(rr1)
yfit2 <- fitted(rr2)
se.fit1 <- sqrt(apply(rr1$m$gradient(), 1, function(x) sum(vcov(rr1)*outer(x,x))))
luconf1 <- yfit1 + outer(se.fit1, qnorm(c(probex, 1 - probex)))
se.fit2 <- sqrt(apply(rr2$m$gradient(), 1, function(x) sum(vcov(rr2)*outer(x,x))))
luconf2 <- yfi...
2007 Sep 25
0
non-linear fitting (nls) and confidence limits
....05
x <- 1:10
y <- rnorm(x, x, .8)
w1 <- rep(1, 10)
w2 <- w1; w2[7:10] <- 0.01 * w2[7:10]
res1 <- nls(y ~ a*x + b, data = list(x = x, y = y), start = list(a = 1, b = 0), weights = w1)
res2 <- nls(y ~ a*x + b, data = list(x = x, y = y), start = list(a = 1, b = 0), weights = w2)
yfit1 <- fitted(res1)
yfit2 <- fitted(res2)
se.fit1 <- sqrt(apply(res1$m$gradient(), 1, function(x) sum(vcov(res1)*outer(x,x))))
luconf1 <- yfit1 + outer(se.fit1, qnorm(c(probex, 1 - probex)))
se.fit2 <- sqrt(apply(res2$m$gradient(), 1, function(x) sum(vcov(res2)*outer(x,x))))
luconf2 <...
2004 Aug 25
3
Beginners Question: Make nlm work
Hello,
I'm new to this and am trying to teach myself some R by plotting
biological data. The growth curve in question is supposed to be fitted
to the Verhulst equation, which may be transcribed as follows:
f(x)=a/(1+((a-0.008)/0.008)*exp(-(b*x)))
- for a known population density (0.008) at t(0).
I am trying to rework the example from "An Introduction to R" (p. 72)
for my case and
2012 Jul 10
1
RGL 3D curvilinear shapes
Dear useRs,
I'm trying to simply fill in the area under a curve using RGL. Here' the set
up:
x <- c(0.75,75.75,150.75,225.75,300.75,375.75,450.75,525.75,600.75,675.75,
0.5,50.5,100.5,150.5,200.5,250.5,300.5,350.5,400.5,450.5,
0.25,25.25,50.25,75.25,100.25,125.25,150.25,175.25,200.25,225.25)
y <- c(0.05,4.91,9.78,14.64,19.51,24.38,29.24,34.11,38.97,43.84,