R boxplot residuals fit model for month computation? Error on cycle()

Question

** Problem **

How box plot can print / show residuals for each month and how to use cycle() to accomplish that this. ALT: Another alternative is to your the innovation residuals (.resid). Seeking to have multiple boxplots by each month with residuals corresponding.

    boxplot(residuals(fit_souvenirs) ~ cycle(residuals(fit_souvenirs)))

ALTernate solution

    boxplot((res$.resid) ~ cycle(res$.resid))

Another ALTernate solution

    model_augmt <- augment(fit_souvenirs, souvenirs$Month)
    
    model_augmt$Month <- month(model_augmt$Month, label = FALSE)
    
    boxplot((model_augmt$.innov) ~ cycle(model_augmt$Month))

The ALT produces this plot:

I have a time bases (x) plot with residuals (y) working.

The following is the code that errors on parameter for boxplot on residuals using cycle:

    model_fit <- souvenirs %>% model(TSLM(Sales ~ trend() + season()))
    res  <- residuals(model_fit)
    boxplot(residuals(model_fit) ~ cycle(residuals(model_fit)))

** Error Code / Message **

    Error in attr(x, "tsp") <- c(1, NROW(x), 1) : invalid time series parameters specified
    11.
    hasTsp(x)
    10.
    tsp(hasTsp(x))
    9.
    cycle.default(residuals(model_fit))
    8.
    cycle(residuals(model_fit))
    7.
    eval(predvars, data, env)
    6.
    eval(predvars, data, env)
    5.
    stats::model.frame.default(formula = residuals(model_fit) ~ cycle(residuals(model_fit)))
    4.
    eval(m, parent.frame())
    3.
    eval(m, parent.frame())
    2.
    boxplot.formula(residuals(model_fit) ~ cycle(residuals(model_fit)))
    1.
    boxplot(residuals(model_fit) ~ cycle(residuals(model_fit)))

** Structure of data **

    tbl_ts [84 x 2] (S3: tbl_ts/tbl_df/tbl/data.frame)
     $ Month: mth [1:84] 1987 Jan, 1987 Feb, 1987 Mar, 1987 Apr, 1987 May, 1987 Jun, 198...
     $ Sales: num [1:84] 1665 2398 2841 3547 3753 ...
     - attr(*, "key")= tbl_df [1 x 1] (S3: tbl_df/tbl/data.frame)
      ..$ .rows: list<int> [1:1] 
      .. ..$ : int [1:84] 1 2 3 4 5 6 7 8 9 10 ...
      .. ..@ ptype: int(0) 
     - attr(*, "index")= chr "Month"
      ..- attr(*, "ordered")= logi TRUE
     - attr(*, "index2")= chr "Month"
     - attr(*, "interval")= interval [1:1] 1M
      ..@ .regular: logi TRUE

    Month       Sales
    1987 Jan    1665
    1987 Feb    2398            
    1987 Mar    2841            
    1987 Apr    3547            
    1987 May    3753            
    1987 Jun    3715

** Dput data **

structure(list(Month = structure(c(6209, 6240, 6268, 6299, 6329, 
6360, 6390, 6421, 6452, 6482, 6513, 6543, 6574, 6605, 6634, 6665, 
6695, 6726, 6756, 6787, 6818, 6848, 6879, 6909, 6940, 6971, 6999, 
7030, 7060, 7091, 7121, 7152, 7183, 7213, 7244, 7274, 7305, 7336, 
7364, 7395, 7425, 7456, 7486, 7517, 7548, 7578, 7609, 7639, 7670, 
7701, 7729, 7760, 7790, 7821, 7851, 7882, 7913, 7943, 7974, 8004, 
8035, 8066, 8095, 8126, 8156, 8187, 8217, 8248, 8279, 8309, 8340, 
8370, 8401, 8432, 8460, 8491, 8521, 8552, 8582, 8613, 8644, 8674, 
8705, 8735), class = c("yearmonth", "vctrs_vctr")), Sales = c(1664.81, 
2397.53, 2840.71, 3547.29, 3752.96, 3714.74, 4349.61, 3566.34, 
5021.82, 6423.48, 7600.6, 19756.21, 2499.81, 5198.24, 7225.14, 
4806.03, 5900.88, 4951.34, 6179.12, 4752.15, 5496.43, 5835.1, 
12600.08, 28541.72, 4717.02, 5702.63, 9957.58, 5304.78, 6492.43, 
6630.8, 7349.62, 8176.62, 8573.17, 9690.5, 15151.84, 34061.01, 
5921.1, 5814.58, 12421.25, 6369.77, 7609.12, 7224.75, 8121.22, 
7979.25, 8093.06, 8476.7, 17914.66, 30114.41, 4826.64, 6470.23, 
9638.77, 8821.17, 8722.37, 10209.48, 11276.55, 12552.22, 11637.39, 
13606.89, 21822.11, 45060.69, 7615.03, 9849.69, 14558.4, 11587.33, 
9332.56, 13082.09, 16732.78, 19888.61, 23933.38, 25391.35, 36024.8, 
80721.71, 10243.24, 11266.88, 21826.84, 17357.33, 15997.79, 18601.53, 
26155.15, 28586.52, 30505.41, 30821.33, 46634.38, 104660.67)), row.names = c(NA, 
-84L), key = structure(list(.rows = structure(list(1:84), ptype = integer(0), class = c("vctrs_list_of", 
"vctrs_vctr", "list"))), row.names = c(NA, -1L), class = c("tbl_df", 
"tbl", "data.frame")), index = structure("Month", ordered = TRUE), index2 = "Month", interval = structure(list(
    year = 0, quarter = 0, month = 1, week = 0, day = 0, hour = 0, 
    minute = 0, second = 0, millisecond = 0, microsecond = 0, 
    nanosecond = 0, unit = 0), .regular = TRUE, class = c("interval", 
"vctrs_rcrd", "vctrs_vctr")), class = c("tbl_ts", "tbl_df", "tbl", 
"data.frame")

Answer 1

A potential solution for innovation residuals order boxplots() by month

    model_augmt <- augment(fit_souvenirs, souvenirs$Month)
    
    model_augmt$Month <- month(model_augmt$Month, label = FALSE)
    model_res_month <- data.frame(inno=model_augmt$.innov, month=model_augmt$Month)
        
    boxplot(inno ~ month, data=model_res_month)