temporary switch to new branch, moving computers

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: arima2
 Title: Likelihood Based Inference for ARIMA Modeling
-Version: 3.3.0.9000
+Version: 3.3.0
 Authors@R: 
     c(
     person("Jesse", 
@@ -35,11 +35,11 @@ Description: Estimating and analyzing auto regressive integrated moving average
     necessary condition for performing likelihood ratio tests. This package 
     relies heavily on the source code of the arima() function of the 'stats' 
     package. For more information, please see Jesse Wheeler and Edward L. 
-    Ionides (2023) <arXiv:2310.01198>.
+    Ionides (2023) <doi:10.48550/arXiv.2310.01198>.
 License: GPL (>= 3)
 Encoding: UTF-8
 Roxygen: list(markdown = TRUE)
-RoxygenNote: 7.3.1
+RoxygenNote: 7.3.2
 Suggests: 
     testthat (>= 3.0.0)
 Config/testthat/edition: 3

R/data.R

@@ -11,5 +11,9 @@
 #'   \item{Date}{`Date` column that records when the observation was made.}
 #'   \item{Average}{`numeric` column representing the average depth in feet.}
 #' }
-#' @source <https://www.glerl.noaa.gov/data/dashboard/data/levels/mGauge/miHuronMog.csv>
+#' @source
+#' NOAA. Annual January levels of lake Michigan-Huron. Great Lakes Environmental Research Laboratory, https://www.glerl.noaa.gov/data/dashboard/data/levels/mGauge/miHuronMog.csv. Accessed 08/24/2023.
+#'
+#' The original url used to obtain the data no longer exists, but a partial subset of the same data can be found at <https://www.greatlakescc.org/en/coordinating-committee-products-and-datasets/> under the subsection: Monthly Mean Water Levels.
+#'
 "miHuron_level"

README.md

@@ -55,6 +55,9 @@ library(arima2)
 #> The following object is masked from 'package:stats':
 #> 
 #>     arima
+```
+
+``` r
 
 set.seed(83131)  
 
@@ -77,9 +80,9 @@ arma <- stats::arima(x, order = c(2, 0, 2))
 ```
 
 In the example above, the resulting log-likelihood of the `stats::arima`
-function is -142.24, and the log-likelihood of the `arima` function is
--139.91. For this particular model and dataset, the random restart
-algorithm implemented in `arima2` improved the model likelihood by 2.33
+function is -139.87, and the log-likelihood of the `arima` function is
+-139.87. For this particular model and dataset, the random restart
+algorithm implemented in `arima2` improved the model likelihood by 0
 log-likelihood units.
 
 Our package creates a new `S3` object that we call `Arima2`, which
@@ -90,9 +93,12 @@ function will return the AR or MA polynomial roots of the fitted model:
 
 ``` r
 ARMApolyroots(arma2, type = 'AR')
-#> [1]  -4.464118+0i -15.209006+0i
+#> [1] -1.650168-1.614921e-19i  2.930118+1.614921e-19i
+```
+
+``` r
 ARMApolyroots(arma2, type = 'MA')
-#> [1] -0.9870024+0.665084i -0.9870024-0.665084i
+#> [1] 1.377623-1.272568e-19i 1.764791+1.272568e-19i
 ```
 
 We have also implemented a `plot.Arima2` function that uses the
@@ -129,19 +135,19 @@ tab_results |> knitr::kable()
 
 |     |      MA0 |      MA1 |      MA2 |      MA3 |      MA4 |
 |:----|---------:|---------:|---------:|---------:|---------:|
-| AR0 | 368.7800 | 302.8397 | 290.2196 | 290.1671 | 291.4220 |
-| AR1 | 319.4248 | 295.5320 | 289.8299 | 291.6313 | 292.9708 |
-| AR2 | 303.4653 | 295.7739 | 291.8176 | 291.5108 | 293.0426 |
-| AR3 | 296.6288 | 296.2828 | 292.9434 | 292.9987 | 293.5101 |
-| AR4 | 295.1954 | 297.1895 | 294.9198 | 294.3391 | 294.9258 |
+| AR0 | 444.5480 | 336.8500 | 299.8703 | 293.5721 | 294.2935 |
+| AR1 | 335.4423 | 288.7580 | 290.0879 | 290.6879 | 292.6741 |
+| AR2 | 318.3194 | 290.3848 | 291.7480 | 292.6826 | 284.1858 |
+| AR3 | 298.9700 | 289.9248 | 291.7193 | 292.4092 | 291.0743 |
+| AR4 | 295.1323 | 291.5070 | 292.0390 | 287.9624 | 289.9623 |
 
 ``` r
 
 P <- which(tab_results == min(tab_results), arr.ind = TRUE)[1] - 1
 Q <- which(tab_results == min(tab_results), arr.ind = TRUE)[2] - 1
 
 print(paste0("p = ", P, "; q = ", Q))
-#> [1] "p = 1; q = 2"
+#> [1] "p = 2; q = 4"
 ```
 
 For more details about this package, please see our arXiv paper:

cran-comments.md

@@ -1,6 +1,6 @@
 ## R CMD check results
 
-0 errors | 0 warnings | 0 note
+0 errors | 0 warnings | 0 notes
 
 ## revdepcheck results