[英]Non-linear least squares in R: Error in eval(predvars, data, env) : object not found
I am trying to fit a gnls
function in R and throws me an error that says: Error in eval(predvars, data, env) : object A not found
Not sure where I am going wrong.我试图在 R 中安装一个
gnls
函数并抛出一个错误,上面写着: Error in eval(predvars, data, env) : object A not found
不确定我哪里出错了。
set.seed(111)
y.size <- rnorm(100,4,1)
p <- rnorm(100,5,1)
df <- data.frame(p, y.size)
# fit generalised nonlinear least squares
require(nlme)
mgnls <- gnls(y.size ~ ((A *((p*K/Ka)-1))-1)* log(p),
start = list(A = c(-1,-10),
K = c(800,3000),
Ka = c(35000,45000)),
data = df)
plot(mgnls) # more homogenous
For anyone needing more info: I'm trying to follow along this method对于任何需要更多信息的人:我正在尝试遵循这种方法
I see there are 2 issues.我看到有2个问题。 First I don't understand the convention
list(A = c(-1,-10), K = c(800,3000),Ka = c(35000,4500))
.首先,我不明白约定
list(A = c(-1,-10), K = c(800,3000),Ka = c(35000,4500))
。 Generally only 1 value is used to initialize the starting value.一般只使用 1 个值来初始化起始值。
Second, your equation defines K/Ka with both values as adjustable parameters.其次,您的方程将 K/Ka 定义为两个值作为可调参数。 This will cause errors since there are an infinite number of values for K and Ka which will evaluate to the same value.
这将导致错误,因为 K 和 Ka 有无数个值,它们将评估为相同的值。 It is better to set one value to a constant or define a new value equal to the ratio.
最好将一个值设置为常数或定义一个等于该比率的新值。
set.seed(111)
y.size <- rnorm(100,4,1)
p <- rnorm(100,5,1)
df <- data.frame(p, y.size)
# fit generalised nonlinear least squares
require(nlme)
mgnls <- gnls(y.size ~ ((A *((p*K_Ka)-1))-1)* log(p),
start = list(A = -5, K_Ka = 0.5),
data=df)
plot(mgnls) # more homogenous
声明:本站的技术帖子网页,遵循CC BY-SA 4.0协议,如果您需要转载,请注明本站网址或者原文地址。任何问题请咨询:yoyou2525@163.com.