Base class for changepoint models
class-mod_cpt.Rd
Create changepoint detection model objects
Arguments
- x
a numeric vector coercible into a
ts
object- tau
indices of the changepoint set
- region_params
A
tibble::tibble()
with one row for each region defined by the changepoint settau
. Each variable represents a parameter estimated in that region.- model_params
A numeric vector of parameters estimated by the model across the entire data set (not just in each region).
- fitted_values
Fitted values returned by the model on the original data set.
- model_name
A
character
vector giving the model's name.- ...
currently ignored
Details
Changepoint detection models know how they were created, on what data set, about the optimal changepoint set found, and the parameters that were fit to the model. Methods for various generic reporting functions are provided.
Examples
cpt <- mod_cpt(CET)
str(cpt)
#> List of 6
#> $ data : Time-Series [1:362] from 1 to 362: 8.87 9.1 9.78 9.52 8.63 9.34 8.29 9.86 8.52 9.51 ...
#> $ tau : int(0)
#> $ region_params: tibble [0 × 0] (S3: tbl_df/tbl/data.frame)
#> Named list()
#> $ model_params : num(0)
#> $ fitted_values: num(0)
#> $ model_name : chr(0)
#> - attr(*, "class")= chr "mod_cpt"
as.ts(cpt)
#> Time Series:
#> Start = 1
#> End = 362
#> Frequency = 1
#> [1] 8.87 9.10 9.78 9.52 8.63 9.34 8.29 9.86 8.52 9.51 9.02 8.96
#> [13] 9.08 8.82 8.38 8.12 7.88 8.84 8.78 8.45 8.76 8.89 8.75 9.05
#> [25] 8.49 7.95 9.16 10.15 8.99 7.86 8.56 8.94 8.17 7.73 8.47 7.67
#> [37] 7.29 8.52 8.05 7.67 8.83 8.60 8.75 9.31 9.09 9.07 8.75 9.82
#> [49] 9.41 9.68 8.74 9.49 9.42 9.14 8.64 9.44 9.44 8.38 9.04 9.29
#> [61] 9.49 9.10 8.91 9.37 9.80 9.28 8.69 9.36 9.97 9.54 9.29 10.07
#> [73] 9.90 9.69 10.50 9.82 9.57 10.33 9.95 9.84 9.21 6.86 9.32 8.38
#> [85] 9.83 8.80 8.85 8.66 9.84 8.79 9.49 9.71 8.47 9.21 9.12 8.87
#> [97] 8.58 8.78 8.97 8.98 10.03 9.85 10.02 9.61 8.95 8.73 8.55 8.66
#> [109] 8.70 8.95 8.81 8.53 8.58 9.17 9.29 9.09 10.11 9.02 9.12 9.23
#> [121] 10.41 9.12 10.23 8.05 9.31 7.85 8.58 8.27 9.31 9.22 8.93 9.46
#> [133] 9.29 9.20 9.13 9.90 8.71 9.02 9.03 9.63 7.92 9.28 9.63 8.98
#> [145] 9.09 9.59 9.00 9.84 8.69 8.86 8.96 8.78 9.69 8.21 8.72 7.78
#> [157] 9.07 7.89 8.89 9.88 9.27 8.56 9.55 10.06 8.40 9.32 9.76 10.09
#> [169] 9.51 10.32 8.18 8.72 10.13 9.49 9.52 10.51 9.57 8.88 8.85 8.10
#> [181] 8.71 8.52 8.75 9.25 9.10 8.60 8.30 10.16 9.26 9.42 9.32 9.10
#> [193] 9.18 9.82 8.41 9.34 8.09 9.10 10.11 9.16 9.64 7.92 9.15 9.21
#> [205] 9.69 8.87 9.72 9.68 9.03 10.40 9.62 9.02 9.07 9.76 9.03 9.33
#> [217] 9.48 9.53 9.19 9.26 7.44 9.10 8.58 9.47 9.04 9.85 8.58 8.74
#> [229] 8.30 8.24 9.02 8.76 8.51 8.18 10.01 9.32 8.70 9.34 9.44 10.10
#> [241] 9.71 9.60 9.15 8.88 9.33 9.02 9.16 9.47 8.88 9.28 8.59 9.20
#> [253] 10.09 9.37 9.83 9.90 8.96 9.20 8.55 9.53 8.53 9.58 10.51 8.70
#> [265] 9.11 9.29 9.20 9.74 9.24 9.59 9.06 9.47 9.02 9.41 9.86 10.03
#> [277] 9.74 9.35 9.59 10.21 9.70 9.06 9.12 9.11 10.05 9.59 10.29 9.46
#> [289] 9.65 10.03 10.64 9.43 9.30 9.12 9.87 9.26 9.33 8.87 10.06 9.45
#> [301] 10.52 9.75 9.95 8.61 8.52 9.48 8.99 9.47 9.64 9.32 9.32 9.60
#> [313] 9.72 9.22 9.57 9.64 10.04 10.10 9.51 9.47 8.85 9.42 9.28 9.86
#> [325] 10.10 9.75 8.90 8.81 9.08 9.80 10.54 10.65 9.58 9.87 9.52 10.29
#> [337] 10.55 9.22 10.56 10.35 10.65 10.32 9.97 10.63 10.54 10.50 10.48 10.87
#> [349] 10.50 9.97 10.14 8.86 10.72 9.72 9.61 10.95 10.31 10.34 10.58 10.68
#> [361] 10.34 10.76
changepoints(cpt)
#> integer(0)