Hello R users,
I am new to R and am wondering if anyone can help me out
with the following issue: I wrote a function to build ts models using
different inputs, but when R displays the call for a model, I cannot tell
which variables
it is using because it shows the arguments instead of the real variables
passed to the function.
(e.g
Call:
lm(formula = dyn(dep ~ lag(dep, -1) + indep)) ---> not what I want to see
lm(formula = dyn(Y ~ lag(Y, -1) + XVARY)) -----> this is what I want to
see
(see simplified version of the code and output below)
Thanks in advance for any help!!
options (scipen=999, digits=7)
library(Hmisc)
library(DAAG)
library(car)
library(MASS)
library(nlme)
library(dyn)
library(zoo)
tdata <- ts(read.table("C:/R/testing/data.csv" ,sep = ",",header=TRUE))
print(tdata)
coeff <- function(dep, indep) {
mod <- dyn$lm(dep ~ lag(dep, -1)+ indep)
summ <- summary(mod)
res <- list(COEF=summ) }
out <- coeff(tdata[ ,"Y"], tdata[ ,"XVARY"]); out
#########output#############
> print(tdata)
Time Series:
Start = 1
End = 20
Frequency = 1
Unit Y XVARY K DWAY
1 1 3 2 4 50
2 2 5 3 9 50
3 3 6 11 22 50
4 4 8 4 7 2
5 5 9 11 11 2
6 6 12 13 13 2
7 7 23 25 12 2
8 8 22 30 31 3
9 9 23 3 3 3
10 10 19 21 21 32
11 11 3 2 4 34
12 12 5 3 9 4
13 13 6 11 22 4
14 14 8 4 7 4
15 15 9 11 11 4
16 16 12 13 13 4
17 17 23 25 12 4
18 18 22 30 31 4
19 19 23 3 3 4
20 20 19 21 21 5
>
> coeff <- function(dep, indep) {
+
+ mod <- dyn$lm(dep ~ lag(dep, -1)+ indep)
+ summ <- summary(mod)
+ res <- list(COEF=summ) }
>
> out <- coeff(tdata[ ,"Y"], tdata[ ,"XVARY"]); out
$COEF
Call:
lm(formula = dyn(dep ~ lag(dep, -1) + indep))
Residuals:
Min 1Q Median 3Q Max
-10.7157 -2.5454 -0.2090 0.8359 7.3292
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 2.6473 2.1952 1.206 0.24538
lag(dep, -1) 0.5506 0.1558 3.535 0.00275 **
indep 0.3033 0.1259 2.408 0.02845 *
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 4.643 on 16 degrees of freedom
(2 observations deleted due to missingness)
Multiple R-squared: 0.6679, Adjusted R-squared: 0.6264
F-statistic: 16.09 on 2 and 16 DF, p-value: 0.0001479
--
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