help(seq)
seq(0,8191)
dim(seq(0,8191)
0
dim(radium)
dim(radium[1])
(radium[1,1]
(radium[1,0]
0
radium[1,0]
radium[1,1]
plot(radium[1,1])
mean(radium)
mean(radium[1])
summary(radium)
sd(radium)
radium[1]
sd(radium[1])
sd(radium[V1])
sapply(radium,mean)
sapply(radium,sd)
hist(radium)
sapply(radium,hist)
x <- seq_along(r)
x <- seq_along(radium)
x
x <- seq_along(radium[V1])
x <- seq_along(radium[1)
x <- seq_along(radium[1])
x
radiu
radium
f <- function(par)
{
m <- par[1]
sd <- par[2]
k <- par[3]
yhat <- k * exp(-0.5 * ((x - m)/sd)^2)
sum((r - rhat)^2)
}
optim(c(15,2,1),f,method="BFGS",control=list(reltol=1e-9))
f <- function(par)
{
m <- par[1]
sd <- par[2]
k <- par[3]
yhat <- k * exp(-0.5 * ((x - m)/sd)^2)
sum((radium - rhat)^2)
}
optim(c(15,2,1),f,method="BFGS",control=list(reltol=1e-9))
f <- function(par)
{
m <- par[1]
sd <- par[2]
k <- par[3]
yhat <- k * exp(-0.5 * ((x - m)/sd)^2)
sum((radium - yhat)^2)
}
optim(c(15,2,1),f,method="BFGS",control=list(reltol=1e-9))
help(unlist)
help(data)
data
data()
radium
row
row.names(radium)
names(radium)
help(row)
Radium <- as.numeric(radium[1,])
Radium
Radium <- as.numeric(radium[2,])
Radium
Radium <- as.numeric(radium[1,])
Radium <- as.numeric(radium[1])
radium[1,
radium[1,]
radium[1,]
radium[1]
Radium <- as.numeric(radium[1])
Radium <- as.numeric(radium[1,2])
Radium
Radium <- as.numeric(radium[1,1])
Radium
radium[1,1]
radium[2,1]
radium[2,]
radium[1,]
radium[0,]
radium
radium["V1"]
radium["V1sdf"]
radium["V1"]
radium[,]
radium[,1]
radium[,0]
radium[,1]
radium[,2]
radium[,]
Radium <- as.numeric(radium[,])
Radium
plot(seq(0,8191),Radium)
plot(seq_along(Radium),Radium)
plot(radium)
mean(radium_
mean(radium)
sapply(radium,mean)
skewness
library(fBasics)
test=c(5,6,7,8,9)
test
test[1:3]=0
test
radium[,70:180]
radium[70:180]
radium[1,70:180]
radium[,70:180]
radium[,]
radium[,][70:180]
radium[,1:3]
radium[,]1:3]
radium[,][1:3]
radium[,][90:180]
radium[,][:180]
radium[,][90]
radium[,][70]
radium[,]
plot(radium[,])
radium$V1
plot(radium$v1)
plot(radium$V1)
library("MASS")
fitdistr(radium,"
fitdistr(radium,"normal")
help(fitdistr)
fitdistr(Radium,"normal")
hist
hist(radium)
hist(Radium)
hist(Radium,prob=TRUE)
dput(radium)
dput(Radium)
plot(Radium)
x <- seq_along(radium)
y <- radium
f
f <- function(par)
m <- par[1]
sd <- par[2]
k <- par[3]
f = function(par)
{
m = par[1]
sd = par[2]
k = par[3]
yhat = k * exp(-0.5 * ((x - m)/sd)^2)
sum((y - yhat)^2)
}
optim(c(15,2,1),f,method="BFGS",control=list(reltol=1e-9)
optim(c(15,2,1),f,method="BFGS",control=list(reltol=1e-9))
optim(c(12,3,2),f,method="BFGS",control=list(reltol=1e-9))
cal = read.table("AM_calibration_curve")
cal
summary(cal)
help(read.table)
cal = read.table("AM_calibration_curve",header=TRUE)
cal
plot(cal)
cal$count
plot(cal$count)
Cal = cal$count
Cal
plot(Cal)
skewness(Cal)
f
g = function(par)
m = par[1]
sd = par[2]
g = function(par)
m = par[1]
g = function(par)
{
m = par[1]
sd = par[2]
k = par[3]
yhat = k * exp(-0.5 * ((x - m)/sd)^2)
sum((y - yhat)^2)
}
x = Cal
x = seq_along(Cal)
x
y = Cal
optim(c(12,3,2),f,method="BFGS",control=list(reltol=1e-9))
tab = data.frame(x,y)
plot(tab)
(res <- nls( r ~ k*exp(-1/2*(x-mu)^2/sigma^2), start=c(mu=15,sigma=5,k=1) , data = tab))
tabv
tab
(res <- nls( r ~ k*exp(-1/2*(x-mu)^2/sigma^2), start=c(mu=15,sigma=5,k=1) , data = tab))
(res <- nls( y ~ k*exp(-1/2*(x-mu)^2/sigma^2), start=c(mu=15,sigma=5,k=1) , data = tab))
(res <- nls( y ~ k*exp(-1/2*(x-mu)^2/sigma^2), start=c(mu=15,sigma=5,k=1) , data = tab))
red
res
summar(res)
summary(res)
(res <- nls( y ~ k*exp(-1/2*(x-mu)^2/sigma^2), start=c(mu=12,sigma=5,k=1) , data = tab))
(res <- nls( y ~ k*exp(-1/2*(x-mu)^2/sigma^2), start=c(mu=12,sigma=3,k=1) , data = tab))
v <- summary(res)$parameters[,"Estimate"]
plot(y~x, data=tab)
plot(function(x) v[3]*exp(-1/2*(x-v[1])^2/v[2]^2),col=2,add=T,xlim=range(tab$x) )
(res <- nls( y ~ k*exp(-1/2*(x-mu)^2/sigma^2), start=c(mu=7500,sigma=200,k=1) , data = tab))
(res <- nls( y ~ k*exp(-1/2*(x-mu)^2/sigma^2), start=c(mu=7500,sigma=20,k=1) , data = tab))
plot(function(x) v[3]*exp(-1/2*(x-v[1])^2/v[2]^2),col=2,add=T,xlim=range(tab$x) )
plot(function(x) v[3]*exp(-1/2*(x-v[1])^2/v[2]^2),col=2,add=T,xlim=range(tab$x) )
plot(y~x, data=tab)
plot(function(x) v[3]*exp(-1/2*(x-v[1])^2/v[2]^2),col=2,add=T,xlim=range(tab$x) )
summary(res)
v <- summary(res)$parameters[,"Estimate"]
plot(r~x, data=tab)
plot(y~x, data=tab)
plot(function(x) v[3]*exp(-1/2*(x-v[1])^2/v[2]^2),col=2,add=T,xlim=range(tab$x) )
plot(function(x) v[3]*exp(-1/2*(x-v[1])^2/v[2]^2),col=5,add=T,xlim=range(tab$x) )
plot(function(x) v[3]*exp(-1/2*(x-v[1])^2/v[2]^2),col=3,add=T,xlim=range(tab$x) )
plot(function(x) v[3]*exp(-1/2*(x-v[1])^2/v[2]^2),col=2,add=T,xlim=range(tab$x) )
function(x) v[3]*exp(-1/2*(x-v[1])^2/v[2]^2),col=2,add=T,xlim=range(tab$x)
function(x) v[3]*exp(-1/2*(x-v[1])^2/v[2]^2)
v[3]*exp(-1/2*(x-v[1])^2/v[2]^2)
plot(v[3]*exp(-1/2*(x-v[1])^2/v[2]^2))
function(x) v[3]*exp(-1/2*(x-v[1])^2/v[2]^2),col=2,add=T,xlim=range(tab$x)
plot(function(x) v[3]*exp(-1/2*(x-v[1])^2/v[2]^2),col=2,add=T,xlim=range(tab$x) )
plot(function(x) v[3]*exp(-1/2*(x-v[1])^2/v[2]^2),col=2,add=T,xlim=range(tab$x) )
help(plot)
plot(v[3]*exp(-1/2*(x-v[1])^2/v[2]^2),type=l)
plot(v[3]*exp(-1/2*(x-v[1])^2/v[2]^2),l)
help plot
help(plot)
plot(v[3]*exp(-1/2*(x-v[1])^2/v[2]^2),type="l")
plot(v[3]*exp(-1/2*(x-v[1])^2/v[2]^2),col=2,type="l")
plot(cal)
plot(v[3]*exp(-1/2*(x-v[1])^2/v[2]^2),col=2,type="l")
plot(y~x, data=tab)
plot(v[3]*exp(-1/2*(x-v[1])^2/v[2]^2),col=2,type="l")
plot(y~x, data=tab)
plot(v[3]*exp(-1/2*(x-v[1])^2/v[2]^2),col=2,type="l",add=TRUE)
plot(v[3]*exp(-1/2*(x-v[1])^2/v[2]^2),col=2,type="l",add=T)
plot(function(x) v[3]*exp(-1/2*(x-v[1])^2/v[2]^2),col=2,add=T,xlim=range(tab$x) )
plot(v[3]*exp(-1/2*(x-v[1])^2/v[2]^2),col=2,type="l",add="T)
plot(v[3]*exp(-1/2*(x-v[1])^2/v[2]^2),col=2,type="l",add=T)
plot(v[3]*exp(-1/2*(x-v[1])^2/v[2]^2),col=2,type="l",add=T,xlim=range(tab$x))
plot(v[3]*exp(-1/2*(x-v[1])^2/v[2]^2),col=2,add=T,xlim=range(tab$x))
plot(function(x) v[3]*exp(-1/2*(x-v[1])^2/v[2]^2),col=2,add=T,xlim=range(tab$x) )
plot(v[3]*exp(-1/2*(x-v[1])^2/v[2]^2),col=2,add=T,xlim=range(tab$x))
plot(function(x) v[3]*exp(-1/2*(x-v[1])^2/v[2]^2),col=2,add=T,xlim=range(tab$x) )
help(plot_
help(plot)
help(plot)
help(plot)
plot(function(x) v[3]*exp(-1/2*(x-v[1])^2/v[2]^2),col=2,add=T)
plot(v[3]*exp(-1/2*(x-v[1])^2/v[2]^2),col=2,add=T,xlim=range(tab$x))
plot(y~x, data=tab)
plot(v[3]*exp(-1/2*(x-v[1])^2/v[2]^2),col=2,add=T,xlim=range(tab$x))
plot(y~x, data=tab)
plot(function(x) v[3]*exp(-1/2*(x-v[1])^2/v[2]^2),col=2,add=T,xlim=range(tab$x))
plot(function(x) v[3]*exp(-1/2*(x-v[1])^2/v[2]^2),col=2,add=T)
plot(y~x, data=tab)
plot(function(x) v[3]*exp(-1/2*(x-v[1])^2/v[2]^2),col=2,add=T)
plot(function(x) v[3]*exp(-1/2*(x-v[1])^2/v[2]^2),col=2,add=T)
plot(function(x) v[3]*exp(-1/2*(x-v[1])^2/v[2]^2),col=2,add=T,xlim=range(tab$x))
plot(y~x, data=tab)
plot(v[3]*exp(-1/2*(x-v[1])^2/v[2]^2),col=2,add=T,xlim=range(tab$x))
plot(y~x, data=tab)
plot(v[3]*exp(-1/2*(x-v[1])^2/v[2]^2),col=2,add=T,xlim=range(tab$x))
plot(y~x, data=tab)
plot(v[3]*exp(-1/2*(x-v[1])^2/v[2]^2),col=2,add=T,xlim=range(tab$x))
plot(y~x, data=tab)
plot(v[3]*exp(-1/2*(x-v[1])^2/v[2]^2),col=2,add=T,xlim=range(tab$x))
plot(y~x, data=tab)
plot(v[3]*exp(-1/2*(x-v[1])^2/v[2]^2),col=2,add=T,xlim=range(tab$x))
plot(y~x, data=tab)
help(nls)
gumbel
library(gumbel)
help(gumbel)
??gumbel
help(maxit)
library(fitdistrplus)
library(fitdist)
fitdist
(res <- nls( y ~ (1/beta)*exp((x-alpha)/beta - exp((x - alpha)/beta)), start=c(alpha=7500,beta=50,) , data = tab))
(res <- nls( y ~ (1/beta)*exp((x-alpha)/beta - exp((x - alpha)/beta)), start=c(alpha=7500,beta=50) , data = tab))
(res <- nls( y ~ (1/beta)*exp((x-alpha)/beta - exp((x - alpha)/beta)), start=c(alpha=7500,beta=100) , data = tab))
(res <- nls( y ~ (1/beta)*exp((x-alpha)/beta - exp((x - alpha)/beta)), start=c(alpha=7500,beta=1) , data = tab))
(res <- nls( y ~ (1/beta)*exp((x-alpha)/beta - exp((x - alpha)/beta)), start=c(alpha=7000,beta=1) , data = tab))
(res <- nls( y ~ (1/beta)*exp((x-alpha)/beta - exp((x - alpha)/beta)), start=c(alpha=7200,beta=10) , data = tab))
plot(y~x, data=tab)
v <- summary(res)$parameters[,"Estimate"]
plot(function(x) (1/v[2])*exp((x-v[1])/v[2] - exp((x - v[1])/v[2]))
plot(function(x) (1/v[2])*exp((x-v[1])/v[2] - exp((x - v[1])/v[2])),col=2,add=T,xlim=range(tab$x))
function(x) (1/v[2])*exp((x-v[1])/v[2] - exp((x - v[1])/v[2]))
(1/v[2])*exp((x-v[1])/v[2] - exp((x - v[1])/v[2]))
(res <- nls( y ~ (1/beta)*exp((x-alpha)/beta - exp((x - alpha)/beta)), start=c(alpha=7200,beta=.1) , data = tab))
(res <- nls( y ~ (1/beta)*exp((x-alpha)/beta - exp((x - alpha)/beta)), start=c(alpha=7200,beta=.15) , data = tab))
(res <- nls( y ~ (1/beta)*exp((x-alpha)/beta - exp((x - alpha)/beta)), start=c(alpha=7200,beta=.01) , data = tab))
(res <- nls( y ~ (1/beta)*exp((x-alpha)/beta - exp((x - alpha)/beta)), start=c(alpha=7200,beta=2) , data = tab))
(res <- nls( y ~ (1/beta)*exp((x-alpha)/beta - exp((x - alpha)/beta)), start=c(alpha=6800,beta=2) , data = tab))
(res <- nls( y ~ (1/beta)*exp((x-alpha)/beta - exp((x - alpha)/beta)), start=c(alpha=6900,beta=2) , data = tab))
(res <- nls( y ~ (1/beta)*exp((x-alpha)/beta - exp((x - alpha)/beta)), start=c(alpha=6950,beta=2) , data = tab))
(res <- nls( y ~ (1/beta)*exp((x-alpha)/beta - exp((x - alpha)/beta)), start=c(alpha=7550,beta=2) , data = tab))
(res <- nls( y ~ (1/beta)*exp((x-alpha)/beta - exp((x - alpha)/beta)), start=c(alpha=7550,beta=3) , data = tab))
(res <- nls( y ~ (1/beta)*exp((x-alpha)/beta - exp((x - alpha)/beta)), start=c(alpha=7550,beta=4) , data = tab))
(res <- nls( y ~ (1/beta)*exp((x-alpha)/beta - exp((x - alpha)/beta)), start=c(alpha=7550,beta=14) , data = tab))
(res <- nls( y ~ (1/beta)*exp((x-alpha)/beta - exp((x - alpha)/beta)), start=c(alpha=7350,beta=14) , data = tab))
(res <- nls( y ~ (1/beta)*exp((x-alpha)/beta - exp((x - alpha)/beta)), start=c(alpha=7350,beta=19) , data = tab))
(res <- nls( y ~ (1/beta)*exp((x-alpha)/beta - exp((x - alpha)/beta)), start=c(alpha=7350,beta=10) , data = tab))
(res <- nls( y ~ (1/beta)*exp((x-alpha)/beta - exp((x - alpha)/beta)), start=c(alpha=7250,beta=10) , data = tab))
(res <- nls( y ~ (1/beta)*exp((x-alpha)/beta - exp((x - alpha)/beta)), start=c(alpha=7254,beta=10) , data = tab))
(res <- nls( y ~ (1/beta)*exp((x-alpha)/beta - exp((x - alpha)/beta)), start=c(alpha=7254,beta=15) , data = tab))
(res <- nls( y ~ (1/beta)*exp((x-alpha)/beta - exp((x - alpha)/beta)), start=c(alpha=7254,beta=19) , data = tab))
(res <- nls( y ~ (1/beta)*exp((x-alpha)/beta - exp((x - alpha)/beta)), start=c(alpha=7254,beta=100) , data = tab))
(res <- nls( y ~ (1/beta)*exp((x-alpha)/beta - exp((x - alpha)/beta)), start=c(alpha=7254,beta=100) , data = tab))
(res <- nls( y ~ (1/beta)*exp((-x-alpha)/beta - exp((-x - alpha)/beta)), start=c(alpha=7254,beta=100) , data = tab))
library(gumbel)
help(fitdistr)
help(fitdistr)
fitdistr(x,"Gamma")
fitdistr(x,"gamma")
fitdistr(y,"gamma")
fitdistr(y~x,"gamma")
x
1
y
help(fitdistr)
x3 <- rweibull(100, shape = 4, scale = 100)
x3
fitdistr(y,"gamma")
fitdistr(y,"weibull"")
fitdistr(y,"weibull")
help(fitdistr)
fitdistr(y,"weibull")
y
fitdistr(y,"gamma")
help(nls)
help(nls.control)
tab
man(nls)
help(nls)
y
help(~)
help("~")
help(formula)
(res <- nls( y ~ k*exp(-1/2*(x-mu)^2/sigma^2), start=c(mu=15,sigma=5,k=1) , data = tab))
(res <- nls( y ~ k*exp(-1/2*(x-mu)^2/sigma^2), start=c(mu=7200,sigma=5,k=1) , data = tab))
(res <- nls( y ~ k*exp(-1/2*(x-mu)^2/sigma^2), start=c(mu=7200,sigma=50,k=1) , data = tab))
(res <- nls( y ~ k*exp(-1/2*(x-mu)^2/sigma^2), start=c(mu=7200,sigma=50,k=1) , y))
(res <- nls( y ~ k*exp(-1/2*(x-mu)^2/sigma^2), start=c(mu=7200,sigma=50,k=1) , cal))
cal
(res <- nls( y ~ k*exp(-1/2*(x-mu)^2/sigma^2), start=c(mu=7200,sigma=50,k=1) , cal))
(res <- nls( y ~ k*exp(-1/2*(x-mu)^2/sigma^2), start=c(mu=7200,sigma=50,k=1) , cal))
help(nls)
help(nls.control)
(res <- nls( y ~ k*exp(-1/2*(x-mu)^2/sigma^2), start=c(mu=7200,sigma=50,k=1) , cal, control=minFactor(0.0002))
(res <- nls( y ~ k*exp(-1/2*(x-mu)^2/sigma^2), start=c(mu=7200,sigma=50,k=1) , cal, control=minFactor(0.0002)))
help(nls.control)
help(nls.control)
nls.control(minFactor=0.0001)
(res <- nls( y ~ k*exp(-1/2*(x-mu)^2/sigma^2), start=c(mu=7200,sigma=50,k=1) , cal))
(res <- nls( y ~ k*exp(-1/2*(x-mu)^2/sigma^2), start=c(mu=7200,sigma=50,k=1) , cal).control(minFactor=0.0001))
help(nls.control)
(res <- nls( y ~ k*exp(-1/2*(x-mu)^2/sigma^2), start=c(mu=7200,sigma=50,k=1) , cal).control(minFactor=1/2048))
nls.control(minFactor=0.0001)
nls.control
1/1024
nls.control(minFactor=0.0001); 
nls.control(minFactor=0.0001) 
nls.control(minFactor=0.0001) bls
nls.control(minFactor=0.0001) nls
nls.control(minFactor=0.0001) nls()
nls.control(minFactor=0.0001); nls()
(res <- nls( y ~ k*exp(-1/2*(x-mu)^2/sigma^2), start=c(mu=7200,sigma=50,k=1) , cal).control(minFactor=1/2048))
(res <- nls( y ~ k*exp(-1/2*(x-mu)^2/sigma^2), start=c(mu=7200,sigma=50,k=1) , cal))
nls.control(minFactor=0.0001); (res <- nls( y ~ k*exp(-1/2*(x-mu)^2/sigma^2), start=c(mu=7200,sigma=50,k=1) , cal))
help(nls.control)
nls.control(minFactor=1/2048)
nls.control(minFactor=1/4096)
nls.control(minFactor=0.0001); (res <- nls( y ~ k*exp(-1/2*(x-mu)^2/sigma^2), start=c(mu=7200,sigma=50,k=1) , cal))
(res <- nls( y ~ k*exp(-1/2*(x-mu)^2/sigma^2), start=c(mu=7200,sigma=50,k=1) , cal))
nls.control(minFactor=1/4096)
(res <- nls( y ~ k*exp(-1/2*(x-mu)^2/sigma^2), start=c(mu=7200,sigma=50,k=1) , cal))
help(nls)
help(nls)
help(nls)
(res <- nls( y ~ k*exp(-1/2*(x-mu)^2/sigma^2), start=c(mu=7200,sigma=50,k=1) , data = cal))
(res <- nls( y ~ k*exp(-1/2*(x-mu)^2/sigma^2), cal, start=c(mu=7200,sigma=50,k=1)))
(res <- nls( y ~ k*exp(-1/2*(x-mu)^2/sigma^2), cal, start=c(mu=7200,sigma=50,k=1),control=list(minFactor=1/4096)))
v <- summary(res)$parameters[,"Estimate"]
plot(y~x, data=tab)
plot(function(x) v[3]*exp(-1/2*(x-v[1])^2/v[2]^2),col=2,add=T,xlim=range(tab$x) )
tab
(res <- nls( y ~ (1/beta)*exp((x-alpha)/beta - exp((x - alpha)/beta)), data=y,start=c(alpha=7200,beta=10),control=list(minFactor=1/4096)))
(res <- nls( y ~ (1/beta)*exp((x-alpha)/beta - exp((x - alpha)/beta)), y,start=c(alpha=7200,beta=10),control=list(minFactor=1/4096)))
(res <- nls( y ~ (1/beta)*exp((x-alpha)/beta - exp((x - alpha)/beta)), cal,start=c(alpha=7200,beta=10),control=list(minFactor=1/4096)))
res
(res <- nls( y ~ (1/beta)*exp((x-alpha)/beta - exp((x - alpha)/beta)), cal,start=c(alpha=7200,beta=10)))
(res <- nls( y ~ (1/beta)*exp((x-alpha)/beta - exp((x - alpha)/beta)), cal,start=c(alpha=7200,beta=1)))
(res <- nls( y ~ (1/beta)*exp((x-alpha)/beta - exp((x - alpha)/beta)), cal,start=c(alpha=7200,beta=1),control=list(minFactor=1/4096)))
help(nls.control)
(res <- nls( y ~ (1/beta)*exp((x-alpha)/beta - exp((x - alpha)/beta)), cal,start=c(alpha=7200,beta=1),control=list(minFactor=1/4096,maxiter=100)))
(res <- nls( y ~ (1/beta)*exp((x-alpha)/beta - exp((x - alpha)/beta)), cal,start=c(alpha=7200,beta=1),control=list(minFactor=1/4096,maxiter=200)))
(res <- nls( y ~ (1/beta)*exp((x-alpha)/beta - exp((x - alpha)/beta)), data=y,start=c(alpha=7200,beta=1),control=list(minFactor=1/8192,maxiter=1000)))
cal
y
(res <- nls( y ~ (1/beta)*exp((x-alpha)/beta - exp((x - alpha)/beta)), data=cal,start=c(alpha=7200,beta=1),control=list(minFactor=1/8192,maxiter=1000)))
(res <- nls( y ~ (1/beta)*exp((x-alpha)/beta - exp((x - alpha)/beta)), data=cal,start=c(alpha=7200,beta=1),control=list(minFactor=1/16384,maxiter=1000)))
(res <- nls( y ~ (1/beta)*exp((x-alpha)/beta - exp((x - alpha)/beta)), data=cal,start=c(alpha=7200,beta=1),control=list(minFactor=1/50000,maxiter=1000)))
(res <- nls( y ~ (1/beta)*exp((x-alpha)/beta - exp((x - alpha)/beta)), data=cal,start=c(alpha=7800,beta=1),control=list(minFactor=1/50000,maxiter=1000)))
(res <- nls( y ~ k*exp(-1/2*(x-mu)^2/sigma^2), start=c(mu=15,sigma=5,k=1) , data = tab))
(res <- nls( y ~ k*exp(-1/2*(x-mu)^2/sigma^2), start=c(mu=7500,sigma=50,k=1) , data = tab)))
(res <- nls( y ~ k*exp(-1/2*(x-mu)^2/sigma^2), start=c(mu=7500,sigma=50,k=1) , data = tab)
(res <- nls( y ~ k*exp(-1/2*(x-mu)^2/sigma^2), start=c(mu=7500,sigma=50,k=1) , data = tab))
(res <- nls( y ~ k*exp(-1/2*(x-mu)^2/sigma^2), start=c(mu=7800,sigma=50,k=1) , data = tab))
help(write)
v[3]*exp(-1/2*(x-v[1])^2/v[2]^2)
write(v[3]*exp(-1/2*(x-v[1])^2/v[2]^2),file="calibration_gaussian")
help(write)
write(v[3]*exp(-1/2*(x-v[1])^2/v[2]^2),file="calibration_gaussian".ncolumns=1)
write(v[3]*exp(-1/2*(x-v[1])^2/v[2]^2),file="calibration_gaussian",ncolumns=1)
plot(cal)
plot(x)
plot(y)
help(plot)
plot(y,xlab="channel")
plot(y,xlab="Channel")
plot(y,xlab="Channel",ylab="Count")
help(plot)
help(axis)
axis(1,labels=FALSe)
axis(1,labels=FALSE)
axis(1,labels=FALSE)
axis(1,labels=TRUE)
axis(2)
box()
rnorm
require(stats)
rnorm
plot(1:4,rnorm(4),axes=FALSe)
plot(1:4,rnorm(4),axes=FALSE)
plot(1:4,rnorm(4),axes=FALSE)
plot(1:4,rnorm(4),axes=FALSE)
plot(1:4,rnorm(4),axes=FALSE)
plot(1:4,rnorm(4),axes=FALSE)
plot(1:4,rnorm(4),axes=FALSE)
plot(y,xlab="Channel",ylab="Count")
lines(v[3]*exp(-1/2*(x-v[1])^2/v[2]^2))
lines(v[3]*exp(-1/2*(x-v[1])^2/v[2]^2),col=red)
lines(v[3]*exp(-1/2*(x-v[1])^2/v[2]^2),col=2)
plot(v[3]*exp(-1/2*(x-v[1])^2/v[2]^2),col=2)
plot(y,xlab="Channel",ylab="Count")
plot(v[3]*exp(-1/2*(x-v[1])^2/v[2]^2),col=2)
plot(y,xlab="Channel",ylab="Count")
points(v[3]*exp(-1/2*(x-v[1])^2/v[2]^2),col=2)
undo
undo()
cancel()
plot(y,xlab="Channel",ylab="Count")
help(lines)
lines(v[3]*exp(-1/2*(x-v[1])^2/v[2]^2),col=2)
help(points)
lines(v[3]*exp(-1/2*(x-v[1])^2/v[2]^2),col=2,lwd=2)
plot(y,xlab="Channel",ylab="Count",lwd=4)
plot(y,xlab="Channel",ylab="Count",lwd=1)
plot(y,xlab="Channel",ylab="Count",lwd=.5)
lines(v[3]*exp(-1/2*(x-v[1])^2/v[2]^2),col=2,lwd=2)
man(hist)
help(hist)
hist(x)
hist(y)
help(hist)
help(hist,freq=TRUE)
hist(y,freq=TRUE)
hist(y)
hist(y,freq=TRUE)
help(hist,freq=TRUE)
help(hist)
hist(x~y,freq=TRUE)
hist(x~y)
x
y
hist(cal)
hist(x)
axis
help(axis)
axis(ylim=c(0,1000))
axis(list(ylim=c(0,1000)))
help(axis)
hist(x,ylim=c(0,1000))
plot(y,xlab="Channel",ylab="Count",lwd=4,pch="x")
plot(y,xlab="Channel",ylab="Count",lwd=4,pch="-")
plot(y,xlab="Channel",ylab="Count",lwd=4,pch="─")
lines(v[3]*exp(-1/2*(x-v[1])^2/v[2]^2),col=2,lwd=2)
abline(v = 7913.63,col=3)
abline(v = 7913.63,col=2)
abline(v = 7913.63,col=1)
abline(v = 7913.63,col=4)
abline(v = 7913.63,col=5)
abline(v = 7913.63,col=4,lwd=2)
abline(v = 7813.63,col=4,lwd=2)
plot(y,xlab="Channel",ylab="Count",lwd=4,pch="─")
lines(v[3]*exp(-1/2*(x-v[1])^2/v[2]^2),col=2,lwd=2)
plot(y,xlab="Channel",ylab="Count",lwd=4,pch="─")
lines(v[3]*exp(-1/2*(x-v[1])^2/v[2]^2),col=2,lwd=2)
abline(v = 7813.63,col=4,lwd=2)
dev.print(pdf,'calibration.pdf')
q()