Displaying 12 results from an estimated 12 matches for "phi3".
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2008 Apr 04
1
Problems with Unit Root testing using ur.df function
...colnames(teststat) <- c('tau2', 'phi1')
}
if (type == "trend") {
result <- lm(z.diff ~ z.lag.1 + 1 + tt + z.diff.lag)
tau <- coef(summary(result))[2, 3]
phi2.reg <- lm(z.diff ~ -1 + z.diff.lag)
phi3.reg <- lm(z.diff ~ z.diff.lag)
phi2 <- anova(phi2.reg, result)$F[2]
phi3 <- anova(phi3.reg, result)$F[2]
teststat <- as.matrix(t(c(tau, phi2, phi3)))
colnames(teststat) <- c('tau3', 'phi2', 'phi3')
}...
2003 Aug 14
1
gnls - Step halving....
...parameters those obtained from the nls
fit. Is a problem of the initial estimates of the
parameters that I get the error or could be something
else?
The code for the nls fit was:
options(contrasts=c("contr.helmert","contr.poly"))
VA1.lis<-nlsList(DRAM~SSlogis(MED,phi1,phi2,phi3)|TRAT,
data=VA1,na.action=na.omit)
The code for the gnls fit was (using a 'difference
parameterization' like SAS):
options(contrasts=c("contr.SAS","contr.poly"))
VA1.gnls<-gnls(DRAM~SSlogis(MED,phi1,phi2,phi3),
data=VA1,params=list(phi1~TRAT,phi2~TRAT,phi3~TRAT),...
2010 Apr 14
0
ur.df ADF Unit Root Test: what is the meaning of phi1 and phi2 test statistic?
...t))[2, 3]
teststat <- as.matrix(t(c(tau, phi1)))
colnames(teststat) <- c("tau2", "phi1")
}
if (type == "trend") {
result <- lm(z.diff ~ z.lag.1 + 1 + tt)
phi2.reg <- lm(z.diff ~ -1)
phi3.reg <- lm(z.diff ~ 1)
phi2 <- anova(phi2.reg, result)$F[2]
phi3 <- anova(phi3.reg, result)$F[2]
tau <- coef(summary(result))[2, 3]
teststat <- as.matrix(t(c(tau, phi2, phi3)))
colnames(teststat) <- c("tau3", &qu...
2011 Feb 06
1
anova() interpretation and error message
...P Biomass
1 334.5567 0.2870000
2 737.5400 0.5713333
3 894.5300 0.6393333
4 782.3800 0.5836667
5 857.5900 0.6003333
6 829.2700 0.5883333
I have fit the data using logistic, Michaelis?Menten, and linear model,
they all give significance.
> fm1 <- nls(Biomass~SSlogis(P, phi1, phi2, phi3), data=Ca.P.Biomass.A)
> fm2 <- nls(Biomass~SSmicmen(P, phi1, phi2), data=Ca.P.Biomass.A)
> fm3 <- lm(Biomass~P, data = Ca.P.Biomass.A)
I hope to compare the difference among the three models, and I using
anova(). As for the example here, the three models seem not have
significant...
2007 Aug 23
1
degrees of freedom question
R2.3, WinXP
Dear all,
I am using the following functions:
f1 = Phi1+(Phi2-Phi1)/(1+exp((log(Phi3)-log(x))/exp(log(Phi4)))
f2 = Phi1+(Phi2-Phi1)/(1+exp((log(Phi3)-log(r)-log(x))/exp(log(Phi4)))
subject to the residual weighting
Var(e[i]) = sigma^2 * abs( E(y) )^(2*Delta)
Here is my question, in steps:
1. Function f1 is separately fitted to two different datasets
corresponding to t...
2017 Oct 18
4
Error messages using nonlinear regression function (nls)
...at = germination[germination$species == "wheat",] ### subset by wheat
scatterplot(Prop ~ end|temp,data=wheat,box=FALSE,reg=FALSE) ### view the data
wheat$temp = as.factor(wheat$temp) ### convert to factor
### First, try to use nlsList
wheat.list <- nlsList(Prop ~ SSlogis(end,phi1,phi2,phi3)| temp,pool=FALSE,data=wheat) ###
### next, try to use lm to estimate starting parameters.
wheat.list = list()
for (i in 1:length(levels(wheat$temp))){
tmpDat = wheat[wheat$temp == levels(wheat$temp)[i],]
tmp.lm <- lm(Prop ~ end,data = tmpDat)
tmp.nls <- nls(Prop ~ theta1 / (1 + exp(...
2010 Nov 18
0
On efficiency, Vectorize and loops
...eta<-(-1)^i * (.9 - .5*i/d)
xi[i,]<-arima.sim(model=list(ar=theta), n, rand.gen = rnorm)
}
rm(i, theta)
#Defining the deterministic base functions 'phi'
phi<-function(u,i){
sqrt(2)*cos(pi*i*u)
}
phi2<-function(i){force(i);
function(u){
sqrt(2)*cos(pi*outer(i,u))
}
}
phi3<-function(u,i){
sqrt(2)*cos(pi*outer(i,u))
}
# Building the random functional process 'X'
X<-lapply(1:n, function(t)local({force(t);
function(u){
X<-0
for (i in 1:d){
X<-X+xi[i,t]*phi(u,i)
}
X<-X
}
}))
X2<-lapply(1:n, function(t)local({force(t)...
2003 Jun 03
1
tseries "adf.test"
I have a question regarding the adf.test command in the tseries library.
I have a vector of time series observations (2265 daily log prices for the
OEX to be exact). I also have this same data in first-differenced form. I
want to test both vectors individually for staionarity with an Augmented
Dickey-Fuller test. I noticed when I use the adf.test command from the
tseries library, the general
2010 Feb 17
0
adf.test help
...ect?
2/ I would like to see critical values also, so I tried with ur.df
> summary(ur.df(x, "trend", lag=0))
<snip>
Value of test-statistic is: -31.8629 338.4156 507.6231
Critical values for test statistics:
1pct 5pct 10pct
tau3 -3.96 -3.41 -3.12
phi2 6.09 4.68 4.03
phi3 8.27 6.25 5.34
Here if I understand correctly, as my first critical value is
significantly less than the 1% critical value I reject the null
hypothesis that x has a unit root, so x is stationary and then mean
reverting.
Thanks,
-Arnaud
2012 May 04
0
ur.df funtion
Dear R users,
I am applying the augmented-Dickey-Fuller Unit Root Test
(ur.df function of the urca package) to a time series of
approximately 50 values.
To be sure I understood what was going on with the ur.df
function, I checked the critical values of the 3 test
statistics (tau, phi2 and phi3 if a trend is included) or
the 2 test statistics (tau and phi1 if only a drift is
included) with the values found in Hamilton (1994) and
Dickey and Fuller (1981).
The ur.df function critical values correspond to Hamilton's
critical values for a sample of size 100. I was surprised
that it does...
2009 Jun 05
1
ADF test
...l standard error: NaN on 0 degrees of freedom
Multiple R-squared: 1, Adjusted R-squared: NaN
F-statistic: NaN on 2 and 0 DF, p-value: NA
Value of test-statistic is: NaN NaN NaN
Critical values for test statistics:
1pct 5pct 10pct
tau3 -4.38 -3.60 -3.24
phi2 8.21 5.68 4.67
phi3 10.61 7.24 5.91
"
Can anyone tell me what is wrong with the codes???The code used is given
below.
Thanx
t=1:length(x)
plot(t,x)
trend = lm(x~t)
abline(lm(x~t))
summary(trend)
library(urca)
x = ts(x, start=1, end = length(x), frequency=1)
x.ct = ur.df(x,lags=0,type='trend')
plot(x....
2017 Oct 20
1
Error messages using nonlinear regression function (nls)
...at",] ### subset by
> > wheat scatterplot(Prop ~ end|temp,data=wheat,box=FALSE,reg=FALSE) ###
> > view the data wheat$temp = as.factor(wheat$temp) ### convert to factor
> >
> > ### First, try to use nlsList
> > wheat.list <- nlsList(Prop ~ SSlogis(end,phi1,phi2,phi3)|
> > temp,pool=FALSE,data=wheat) ###
> >
> > ### next, try to use lm to estimate starting parameters.
> > wheat.list = list()
> >
> > for (i in 1:length(levels(wheat$temp))){
> > tmpDat = wheat[wheat$temp == levels(wheat$temp)[i],]
> > tmp.lm <...