forecasting - Error in R tbats function -

i have 548 weeks of data , trying use tbats little success. following error:

error in checkforremoteerrors(val) :    3 nodes produced errors; first error: function cannot evaluated @ initial parameters 

my data:

weeklyu <-structure(list(v1 = c(18594l, 13593l, 9854l, 12040l, 12920l,  13302l, 12500l, 13073l, 13801l, 12895l, 13199l, 21568l, 19848l,  13418l, 13188l, 13560l, 21327l, 17724l, 11875l, 12475l, 15130l,  14497l, 16289l, 22388l, 17091l, 21104l, 19579l, 18432l, 13234l,  16728l, 15368l, 18105l, 14715l, 16763l, 16788l, 15701l, 17331l,  18725l, 24336l, 16186l, 14299l, 15144l, 17444l, 19384l, 17035l,  18611l, 25946l, 32773l, 41676l, 59446l, 74874l, 19839l, 18325l,  17417l, 14025l, 15225l, 15323l, 16075l, 14756l, 15567l, 19416l,  15190l, 14349l, 19137l, 17714l, 22033l, 20182l, 16660l, 23325l,  19769l, 19465l, 16379l, 20762l, 19084l, 17395l, 21461l, 17616l,  25190l, 22671l, 21138l, 15302l, 19633l, 18951l, 20609l, 16493l,  18680l, 19583l, 18474l, 17654l, 20000l, 26003l, 17507l, 16547l,  18051l, 18627l, 19451l, 17682l, 19522l, 26240l, 33652l, 44835l,  59187l, 84620l, 32522l, 19829l, 17226l, 14330l, 15146l, 16043l,  16891l, 14569l, 14405l, 15919l, 13953l, 13014l, 16951l, 19543l,  23729l, 21614l, 14385l, 18847l, 17892l, 13140l, 11989l, 31371l,  32555l, 27598l, 29342l, 20787l, 30886l, 31296l, 26188l, 18586l,  22866l, 23160l, 26679l, 19641l, 20722l, 23915l, 16546l, 21480l,  21822l, 32611l, 21739l, 19410l, 17950l, 20800l, 22238l, 22667l,  21158l, 29635l, 38873l, 51334l, 67618l, 102150l, 56709l, 27771l,  20496l, 15617l, 17840l, 19616l, 19477l, 19703l, 17789l, 22365l,  21165l, 19706l, 30054l, 28939l, 26935l, 24446l, 18319l, 27419l,  43941l, 21068l, 18139l, 18385l, 22229l, 23650l, 28577l, 22497l,  27637l, 32822l, 28892l, 22691l, 23788l, 23727l, 22212l, 19853l,  21458l, 24941l, 23761l, 22393l, 20688l, 30884l, 30939l, 19373l,  19446l, 22363l, 25349l, 24333l, 24361l, 25849l, 40634l, 52033l,  68422l, 112772l, 84959l, 31343l, 24789l, 22639l, 19352l, 22176l,  21494l, 20161l, 17960l, 22985l, 24113l, 20326l, 20605l, 23159l,  28641l, 34736l, 22614l, 28310l, 33962l, 23836l, 21205l, 19933l,  23414l, 24127l, 25762l, 27898l, 27069l, 37598l, 32451l, 31210l,  24470l, 26281l, 23764l, 24506l, 21034l, 27204l, 29456l, 26162l,  25692l, 33738l, 32727l, 22314l, 22937l, 23974l, 28979l, 26481l,  27885l, 28264l, 41185l, 53924l, 62340l, 109928l, 97952l, 33023l,  27537l, 19913l, 18757l, 24361l, 22391l, 22402l, 19865l, 23339l,  23995l, 19874l, 19599l, 24435l, 31449l, 24959l, 18649l, 22280l,  32005l, 23227l, 18678l, 17894l, 23540l, 26109l, 26178l, 36432l,  30085l, 34126l, 28556l, 22603l, 21849l, 27871l, 22422l, 23984l,  19919l, 26152l, 28189l, 23459l, 20078l, 28310l, 31234l, 22394l,  20988l, 21401l, 28869l, 29915l, 25649l, 28483l, 40985l, 56049l,  65034l, 107110l, 103296l, 28677l, 23472l, 21035l, 18810l, 21639l,  22750l, 22675l, 19938l, 20674l, 24204l, 18657l, 20852l, 24986l,  26861l, 34310l, 22236l, 32884l, 37194l, 24933l, 18839l, 19396l,  24473l, 27922l, 24582l, 30348l, 23238l, 33199l, 31392l, 24778l,  20016l, 28230l, 24011l, 21890l, 20894l, 25797l, 29816l, 23384l,  21111l, 23517l, 30393l, 32004l, 20316l, 19941l, 25712l, 27371l,  23985l, 26508l, 39417l, 56225l, 65534l, 106220l, 135823l, 34772l,  24237l, 21064l, 19184l, 22146l, 25044l, 21753l, 21482l, 22178l,  25718l, 21384l, 21099l, 26945l, 33711l, 35273l, 24807l, 22027l,  34099l, 29842l, 21348l, 18802l, 25595l, 27276l, 24056l, 29279l,  24938l, 36060l, 33213l, 30601l, 20955l, 24773l, 28693l, 31301l,  24287l, 24545l, 30910l, 27261l, 23929l, 25167l, 34285l, 35096l,  21831l, 22137l, 25630l, 26853l, 25871l, 27499l, 36479l, 52402l,  58148l, 83033l, 122756l, 58313l, 26249l, 22310l, 17733l, 19202l,  22390l, 20969l, 20553l, 17860l, 24034l, 20915l, 19864l, 25003l,  31461l, 30302l, 21518l, 21273l, 24785l, 28366l, 26014l, 20288l,  21098l, 23394l, 21124l, 26181l, 24367l, 33042l, 32558l, 27164l,  20895l, 24235l, 26494l, 26734l, 17734l, 19397l, 25407l, 23536l,  21434l, 22248l, 34186l, 25554l, 18707l, 17292l, 19123l, 23300l,  21337l, 23136l, 27681l, 49923l, 59344l, 77552l, 97665l, 68414l,  27532l, 21217l, 16269l, 17607l, 22626l, 21087l, 20776l, 15611l,  22448l, 20070l, 18562l, 22027l, 25401l, 33810l, 21264l, 28131l,  28179l, 39713l, 23450l, 20752l, 23593l, 27141l, 25511l, 30010l,  23526l, 29145l, 34520l, 32609l, 30214l, 25018l, 26091l, 22625l,  21205l, 21550l, 29100l, 27555l, 21273l, 22519l, 32719l, 29749l,  29160l, 19621l, 23631l, 27312l, 26380l, 25949l, 30285l, 46186l,  59925l, 71215l, 120941l, 87855l, 32558l, 23906l, 22984l, 19685l,  23324l, 20996l, 21947l, 17577l, 23871l, 22242l, 18914l, 18821l,  24463l, 33096l, 27962l, 20848l, 26917l, 34725l, 21951l, 18351l,  17952l, 24975l, 23563l, 23275l, 29248l, 28011l, 37056l)), .names = "v1", class = "data.frame", row.names = c(na,  -548l)) 

the data has 53 weeks in leap year , there 2 seasonalities present: 52.25 , 209.

weeklyts <- msts(weeklyu, seasonal.period=c(52.25,209), ts.frequency=52.25) 

i try:

weeklytbat <- tbats(weeklyts) 

and error above.

it work if set seasonal.periods c(52,209) or c(52.3,209) or c(52.2501,209).

any appreciated

this bug in function caused 1 seasonal period being small multiple of other. fixed in github version @ https://github.com/robjhyndman/forecast. cran version updated in due course.