# I have a daily  series of  count of transactions data i want to decompose
and forecast.
d<-c(723, 772, 967, 897, 621, 684, 722, 764, 856, 819,
678, 708, 698, 832, 928, 834, 649, 676, 635, 729, 778, 817, 616,
598, 605, 851, 822, 791, 678, 703, 716, 834, 872, 831, 641, 610,
699, 840, 901, 789, 620, 744, 644, 816, 805, 726, 565, 613, 733,
802, 744, 791, 624, 671, 729, 756, 828, 782, 545, 640, 691, 786,
818, 795, 622, 661, 644, 748, 805, 793, 615, 597, 584, 634, 655,
497, 330, 789, 668, 659, 779, 678, 524, 623, 592, 710, 703, 660,
586, 721, 1509, 925, 962, 690, 610, 772, 752, 609, 572, 926,
843, 737, 672, 617, 535, 611, 629, 781, 617, 534, 527, 552, 723,
777, 640, 592, 540, 584, 756, 801, 676, 618, 509, 530, 746, 739)

# I convert it into a time series as follows'

d.ts<-ts(d,start=c(2014,as.POSIXlt("2014-01-02")$yday+1),frequency=365)

decompose(d.ts)
Error in decompose(d.ts) : time series has no or less than 2 periods

# How do i fix the period issue if i want to fix the period as weekly to
coincide with  6 days operation in a week where the data was extracted.

Charles.

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