2
$\begingroup$

I'm trying to forecast items, which are extremely seasonal. E.g. I'm trying to forecast seasonal Fruits (like fresh Oranges which available only in winter).

The issue with these data, for each year I've 3-6 months of data only.

My question is if someone can suggest me some methodology on how to forecast in these cases.

The example data:

Date        Output
7/4/2014    2,649
7/5/2014    3,296
7/6/2014    4,542
7/7/2014    2,258
7/8/2014    5,061
7/9/2014    2,028
7/10/2014   2,710
7/11/2014   5,470
7/12/2014   9,231
7/13/2014   5,123
7/14/2014   8,830
7/15/2014   5,127
7/16/2014   3,350
7/17/2014   4,273
7/18/2014   8,673
7/19/2014   6,407
7/20/2014   9,818
7/21/2014   8,261
7/22/2014   3,514
7/23/2014   5,783
7/24/2014   5,902
7/25/2014   2,013
7/26/2014   6,244
7/27/2014   5,404
7/28/2014   3,842
7/29/2014   5,050
7/30/2014   3,945
7/31/2014   8,470
8/1/2014    2,879
8/2/2014    8,757
8/3/2014    6,766
8/4/2014    2,907
8/5/2014    4,272
8/6/2014    5,474
8/7/2014    3,858
8/8/2014    9,275
8/9/2014    4,144
8/10/2014   7,376
8/11/2014   8,891
8/12/2014   3,353
8/13/2014   9,902
8/14/2014   3,770
8/15/2014   8,534
8/16/2014   4,498
8/17/2014   8,106
8/18/2014   6,332
8/19/2014   7,585
8/20/2014   8,795
8/21/2014   9,567
8/22/2014   4,255
8/23/2014   7,543
8/24/2014   8,160
8/25/2014   8,795
8/26/2014   3,657
8/27/2014   2,152
8/28/2014   9,910
8/29/2014   8,808
8/30/2014   9,505
8/31/2014   5,824
9/1/2014    9,660
9/2/2014    7,262
9/3/2014    4,615
9/4/2014    3,790
9/5/2014    4,294
9/6/2014    2,856
9/7/2014    9,847
9/8/2014    9,848
9/9/2014    4,576
9/10/2014   7,950
9/11/2014   8,913
9/12/2014   6,200
9/13/2014   5,095
9/14/2014   5,521
9/15/2014   3,560
9/16/2014   4,824
9/17/2014   9,548
9/18/2014   6,101
9/19/2014   2,164
9/20/2014   5,612
9/21/2014   3,283
9/22/2014   4,030
9/23/2014   7,627
9/24/2014   2,276
9/25/2014   7,062
9/26/2014   7,064
9/27/2014   6,927
9/28/2014   3,738
9/29/2014   8,554
9/30/2014   8,409
10/1/2014   0
10/2/2014   0
10/3/2014   0
10/4/2014   0
10/5/2014   0
10/6/2014   0
10/7/2014   0
10/8/2014   0
10/9/2014   0
10/10/2014  0
10/11/2014  0
10/12/2014  0
10/13/2014  0
10/14/2014  0
10/15/2014  0
10/16/2014  0
10/17/2014  0
10/18/2014  0
10/19/2014  0
10/20/2014  0
10/21/2014  0
10/22/2014  0
10/23/2014  0
10/24/2014  0
10/25/2014  0
10/26/2014  0
10/27/2014  0
10/28/2014  0
10/29/2014  0
10/30/2014  0
10/31/2014  0
11/1/2014   0
11/2/2014   0
11/3/2014   0
11/4/2014   0
11/5/2014   0
11/6/2014   0
11/7/2014   0
11/8/2014   0
11/9/2014   0
11/10/2014  0
11/11/2014  0
11/12/2014  0
11/13/2014  0
11/14/2014  0
11/15/2014  0
11/16/2014  0
11/17/2014  0
11/18/2014  0
11/19/2014  0
11/20/2014  0
11/21/2014  0
11/22/2014  0
11/23/2014  0
11/24/2014  0
11/25/2014  0
11/26/2014  0
11/27/2014  0
11/28/2014  0
11/29/2014  0
11/30/2014  0
12/1/2014   0
12/2/2014   0
12/3/2014   0
12/4/2014   0
12/5/2014   0
12/6/2014   0
12/7/2014   0
12/8/2014   0
12/9/2014   0
12/10/2014  0
12/11/2014  0
12/12/2014  0
12/13/2014  0
12/14/2014  0
12/15/2014  0
12/16/2014  0
12/17/2014  0
12/18/2014  0
12/19/2014  0
12/20/2014  0
12/21/2014  0
12/22/2014  0
12/23/2014  0
12/24/2014  0
12/25/2014  0
12/26/2014  0
12/27/2014  0
12/28/2014  0
12/29/2014  0
12/30/2014  0
12/31/2014  0
1/1/2015    0
1/2/2015    0
1/3/2015    0
1/4/2015    0
1/5/2015    0
1/6/2015    0
1/7/2015    0
1/8/2015    0
1/9/2015    0
1/10/2015   0
1/11/2015   0
1/12/2015   0
1/13/2015   0
1/14/2015   0
1/15/2015   0
1/16/2015   0
1/17/2015   0
1/18/2015   0
1/19/2015   0
1/20/2015   0
1/21/2015   0
1/22/2015   0
1/23/2015   0
1/24/2015   0
1/25/2015   0
1/26/2015   0
1/27/2015   0
1/28/2015   0
1/29/2015   0
1/30/2015   0
1/31/2015   0
2/1/2015    0
2/2/2015    0
2/3/2015    0
2/4/2015    0
2/5/2015    0
2/6/2015    0
2/7/2015    0
2/8/2015    0
2/9/2015    0
2/10/2015   0
2/11/2015   0
2/12/2015   0
2/13/2015   0
2/14/2015   0
2/15/2015   0
2/16/2015   0
2/17/2015   0
2/18/2015   0
2/19/2015   0
2/20/2015   0
2/21/2015   0
2/22/2015   0
2/23/2015   0
2/24/2015   0
2/25/2015   0
2/26/2015   0
2/27/2015   0
2/28/2015   0
3/1/2015    7,076
3/2/2015    7,357
3/3/2015    5,683
3/4/2015    9,925
3/5/2015    9,639
3/6/2015    5,753
3/7/2015    8,091
3/8/2015    6,821
3/9/2015    9,371
3/10/2015   6,821
3/11/2015   8,125
3/12/2015   3,026
3/13/2015   3,520
3/14/2015   3,577
3/15/2015   6,931
3/16/2015   5,998
3/17/2015   7,957
3/18/2015   7,142
3/19/2015   7,736
3/20/2015   9,574
3/21/2015   9,878
3/22/2015   4,102
3/23/2015   9,339
3/24/2015   3,719
3/25/2015   3,635
3/26/2015   5,115
3/27/2015   7,315
3/28/2015   9,960
3/29/2015   3,584
3/30/2015   7,115
3/31/2015   6,516
4/1/2015    6,711
4/2/2015    9,265
4/3/2015    7,162
4/4/2015    6,411
4/5/2015    2,438
4/6/2015    4,602
4/7/2015    2,895
4/8/2015    4,687
4/9/2015    7,824
4/10/2015   2,425
4/11/2015   2,967
4/12/2015   6,913
4/13/2015   9,851
4/14/2015   2,741
4/15/2015   7,713
4/16/2015   9,714
4/17/2015   9,342
4/18/2015   4,029
4/19/2015   9,408
4/20/2015   7,665
4/21/2015   6,290
4/22/2015   8,380
4/23/2015   5,671
4/24/2015   3,818
4/25/2015   7,296
4/26/2015   2,163
4/27/2015   5,696
4/28/2015   9,080
4/29/2015   7,361
4/30/2015   7,883
5/1/2015    6,606
5/2/2015    4,913
5/3/2015    9,351
5/4/2015    4,605
5/5/2015    3,755
5/6/2015    5,112
5/7/2015    3,135
5/8/2015    4,900
5/9/2015    9,814
5/10/2015   7,849
5/11/2015   6,413
5/12/2015   2,217
5/13/2015   9,146
5/14/2015   2,081
5/15/2015   3,933
5/16/2015   2,647
5/17/2015   2,892
5/18/2015   8,625
5/19/2015   8,260
5/20/2015   7,280
5/21/2015   5,269
5/22/2015   8,328
5/23/2015   8,466
5/24/2015   6,096
5/25/2015   8,534
5/26/2015   2,617
5/27/2015   7,439
5/28/2015   8,054
5/29/2015   7,371
5/30/2015   5,665
5/31/2015   6,916
6/1/2015    3,472
6/2/2015    8,201
6/3/2015    5,218
6/4/2015    7,879
6/5/2015    4,362
6/6/2015    2,181
6/7/2015    4,144
6/8/2015    2,030
6/9/2015    4,645
6/10/2015   7,860
6/11/2015   2,363
6/12/2015   6,978
6/13/2015   5,129
6/14/2015   4,762
6/15/2015   9,084
6/16/2015   9,906
6/17/2015   7,857
6/18/2015   5,360
6/19/2015   4,083
6/20/2015   7,243
6/21/2015   3,790
6/22/2015   8,280
6/23/2015   7,146
6/24/2015   6,852
6/25/2015   3,686
6/26/2015   4,338
6/27/2015   3,408
6/28/2015   9,358
6/29/2015   7,280
6/30/2015   7,338
7/1/2015    2,207
7/2/2015    7,256
7/3/2015    7,877
7/4/2015    6,023
7/5/2015    3,274
7/6/2015    4,134
7/7/2015    6,304
7/8/2015    2,417
7/9/2015    7,883
7/10/2015   3,595
7/11/2015   4,798
7/12/2015   3,099
7/13/2015   9,023
7/14/2015   7,370
7/15/2015   4,490
7/16/2015   8,133
7/17/2015   2,368
7/18/2015   9,577
7/19/2015   8,609
7/20/2015   8,088
7/21/2015   4,232
7/22/2015   4,101
7/23/2015   9,036
7/24/2015   7,206
7/25/2015   5,515
7/26/2015   9,525
7/27/2015   4,653
7/28/2015   3,670
7/29/2015   8,992
7/30/2015   3,860
7/31/2015   5,457
8/1/2015    4,517
8/2/2015    8,389
8/3/2015    7,009
8/4/2015    9,636
8/5/2015    5,311
8/6/2015    4,823
8/7/2015    2,833
8/8/2015    9,521
8/9/2015    7,145
8/10/2015   9,106
8/11/2015   6,146
8/12/2015   6,148
8/13/2015   3,038
8/14/2015   6,047
8/15/2015   3,146
8/16/2015   9,175
8/17/2015   9,530
8/18/2015   4,180
8/19/2015   9,223
8/20/2015   8,647
8/21/2015   7,070
8/22/2015   3,545
8/23/2015   8,144
8/24/2015   7,817
8/25/2015   6,317
8/26/2015   5,719
8/27/2015   8,430
8/28/2015   9,033
8/29/2015   7,022
8/30/2015   4,775
8/31/2015   4,071
9/1/2015    8,555
9/2/2015    8,155
9/3/2015    6,939
9/4/2015    9,689
9/5/2015    2,867
9/6/2015    9,732
9/7/2015    4,409
9/8/2015    5,205
9/9/2015    2,335
9/10/2015   3,501
9/11/2015   6,268
9/12/2015   9,721
9/13/2015   9,213
9/14/2015   3,739
9/15/2015   5,681
9/16/2015   2,374
9/17/2015   6,281
9/18/2015   5,860
9/19/2015   5,312
9/20/2015   7,203
9/21/2015   8,493
9/22/2015   9,876
9/23/2015   7,963
9/24/2015   5,112
9/25/2015   2,525
9/26/2015   9,804
9/27/2015   8,181
9/28/2015   9,582
9/29/2015   9,697
9/30/2015   7,825
10/1/2015   0
10/2/2015   0
10/3/2015   0
10/4/2015   0
10/5/2015   0
10/6/2015   0
10/7/2015   0
10/8/2015   0
10/9/2015   0
10/10/2015  0
10/11/2015  0
10/12/2015  0
10/13/2015  0
10/14/2015  0
10/15/2015  0
10/16/2015  0
10/17/2015  0
10/18/2015  0
10/19/2015  0
10/20/2015  0
10/21/2015  0
10/22/2015  0
10/23/2015  0
10/24/2015  0
10/25/2015  0
10/26/2015  0
10/27/2015  0
10/28/2015  0
10/29/2015  0
10/30/2015  0
10/31/2015  0
11/1/2015   0
11/2/2015   0
11/3/2015   0
11/4/2015   0
11/5/2015   0
11/6/2015   0
11/7/2015   0
11/8/2015   0
11/9/2015   0
11/10/2015  0
11/11/2015  0
11/12/2015  0
11/13/2015  0
11/14/2015  0
11/15/2015  0
11/16/2015  0
11/17/2015  0
11/18/2015  0
11/19/2015  0
11/20/2015  0
11/21/2015  0
11/22/2015  0
11/23/2015  0
11/24/2015  0
11/25/2015  0
11/26/2015  0
11/27/2015  0
11/28/2015  0
11/29/2015  0
11/30/2015  0
12/1/2015   0
12/2/2015   0
12/3/2015   0
12/4/2015   0
12/5/2015   0
12/6/2015   0
12/7/2015   0
12/8/2015   0
12/9/2015   0
12/10/2015  0
12/11/2015  0
12/12/2015  0
12/13/2015  0
12/14/2015  0
12/15/2015  0
12/16/2015  0
12/17/2015  0
12/18/2015  0
12/19/2015  0
12/20/2015  0
12/21/2015  0
12/22/2015  0
12/23/2015  0
12/24/2015  0
12/25/2015  0
12/26/2015  0
12/27/2015  0
12/28/2015  0
12/29/2015  0
12/30/2015  0
12/31/2015  0
1/1/2016    0
1/2/2016    0
1/3/2016    0
1/4/2016    0
1/5/2016    0
1/6/2016    0
1/7/2016    0
1/8/2016    0
1/9/2016    0
1/10/2016   0
1/11/2016   0
1/12/2016   0
1/13/2016   0
1/14/2016   0
1/15/2016   0
1/16/2016   0
1/17/2016   0
1/18/2016   0
1/19/2016   0
1/20/2016   0
1/21/2016   0
1/22/2016   0
1/23/2016   0
1/24/2016   0
1/25/2016   0
1/26/2016   0
1/27/2016   0
1/28/2016   0
1/29/2016   0
1/30/2016   0
1/31/2016   0
2/1/2016    0
2/2/2016    0
2/3/2016    0
2/4/2016    0
2/5/2016    0
2/6/2016    0
2/7/2016    0
2/8/2016    0
2/9/2016    0
2/10/2016   0
2/11/2016   0
2/12/2016   0
2/13/2016   0
2/14/2016   0
2/15/2016   0
2/16/2016   0
2/17/2016   0
2/18/2016   0
2/19/2016   0
2/20/2016   0
2/21/2016   0
2/22/2016   0
2/23/2016   0
2/24/2016   0
2/25/2016   0
2/26/2016   0
2/27/2016   0
2/28/2016   0
2/29/2016   0
3/1/2016    5,930
3/2/2016    6,733
3/3/2016    8,316
3/4/2016    2,516
3/5/2016    4,602
3/6/2016    8,295
3/7/2016    7,614
3/8/2016    2,515
3/9/2016    2,616
3/10/2016   3,381
3/11/2016   2,795
3/12/2016   9,129
3/13/2016   4,035
3/14/2016   9,854
3/15/2016   6,788
3/16/2016   3,513
3/17/2016   5,064
3/18/2016   2,924
3/19/2016   9,227
3/20/2016   7,546
3/21/2016   9,271
3/22/2016   3,194
3/23/2016   7,150
3/24/2016   6,997
3/25/2016   9,319
3/26/2016   2,323
3/27/2016   2,154
3/28/2016   7,914
3/29/2016   9,176
3/30/2016   8,608
3/31/2016   3,414
4/1/2016    8,555
4/2/2016    3,103
4/3/2016    9,997
4/4/2016    2,177
4/5/2016    9,627
4/6/2016    2,485
4/7/2016    2,688
4/8/2016    3,983
4/9/2016    9,004
4/10/2016   4,097
4/11/2016   2,402
4/12/2016   7,424
4/13/2016   5,642
4/14/2016   4,294
4/15/2016   9,994
4/16/2016   2,703
4/17/2016   6,701
4/18/2016   3,710
4/19/2016   6,471
4/20/2016   2,084
4/21/2016   9,836
4/22/2016   2,575
4/23/2016   5,644
4/24/2016   8,902
4/25/2016   9,463
4/26/2016   9,580
4/27/2016   9,746
4/28/2016   6,423
4/29/2016   5,747
4/30/2016   6,746
5/1/2016    9,509
5/2/2016    9,031
5/3/2016    9,006
5/4/2016    7,539
5/5/2016    9,387
5/6/2016    10,000
5/7/2016    4,013
5/8/2016    6,383
5/9/2016    9,679
5/10/2016   7,579
5/11/2016   2,500
5/12/2016   4,373
5/13/2016   9,109
5/14/2016   6,948
5/15/2016   9,183
5/16/2016   2,294
5/17/2016   4,633
5/18/2016   8,480
5/19/2016   6,685
5/20/2016   7,181
5/21/2016   4,841
5/22/2016   7,685
5/23/2016   4,302
5/24/2016   5,853
5/25/2016   5,279
5/26/2016   4,716
5/27/2016   9,318
5/28/2016   6,669
5/29/2016   5,705
5/30/2016   8,721
5/31/2016   2,799
6/1/2016    8,317
6/2/2016    4,878
6/3/2016    8,146
6/4/2016    6,454
6/5/2016    2,736
6/6/2016    6,199
6/7/2016    4,809
6/8/2016    9,628
6/9/2016    9,359
6/10/2016   8,648
6/11/2016   9,478
6/12/2016   5,989
6/13/2016   4,277
6/14/2016   8,480
6/15/2016   7,705
6/16/2016   5,120
6/17/2016   7,461
6/18/2016   9,634
6/19/2016   5,379
6/20/2016   7,839
6/21/2016   5,897
6/22/2016   2,576
6/23/2016   3,643
6/24/2016   7,977
6/25/2016   3,255
6/26/2016   9,900
6/27/2016   4,179
6/28/2016   8,502
6/29/2016   8,439
6/30/2016   4,186
7/1/2016    4,036
7/2/2016    8,595
7/3/2016    7,318
7/4/2016    7,503
Improve this question
$\endgroup$
2
  • $\begingroup$ Is it true that you have only 3-6 months of data, or do you have 3-6 months of nonzero data and you know (or can safely assume) the values for the remaining months are zero? $\endgroup$ – whuber♦ Mar 10 '17 at 23:23
  • $\begingroup$ @whuber: THanks for your comment. I just have 3-6 months of nonzero data. Rest are zero. $\endgroup$ – Beta Mar 11 '17 at 6:23
1
$\begingroup$

If you have say 5 consistent months of data per year set up your ARIMA model using a seasonality of 5. I f you have some years with only 4 data points put a "0" in for the missing point. The whole idea is to lock in some fixed frequency of measurement say 5 . If you have 8 pseudo years of data then you should have 40 values in this example. This happens normally with products that are only sold in certain months of the year like Octoberfest beers.

Improve this answer
$\endgroup$
7
  • $\begingroup$ Thanks for your reply. I tried this, but the results are not very interesting. So was looking for some other options. $\endgroup$ – Beta Mar 11 '17 at 6:25
  • $\begingroup$ why don't you post an example of your data ( real or constructed) and I will try and help. $\endgroup$ – IrishStat Mar 11 '17 at 9:17
  • $\begingroup$ Thanks a lot for helping me with the problem. I've update the example data in the question. $\endgroup$ – Beta Mar 11 '17 at 10:55
  • 1
    $\begingroup$ It would appear that you have daily data with 214 observations per year. I would create a data set that has 429 values ( your non-zero values) and specify a seasonality/frequency of 214 . $\endgroup$ – IrishStat Mar 11 '17 at 14:09
  • $\begingroup$ Thanks a ton IrishStat! You have been extremely helpful. $\endgroup$ – Beta Mar 11 '17 at 14:35

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