[R] Unable to Understand Results of pglm function
Paul Bernal
p@u|bern@|07 @end|ng |rom gm@||@com
Tue Apr 23 22:44:29 CEST 2019
Dear Yves,
Hope you are doing great. I have been testing the pglm function from the
pglm package, in order to fit a logit regression to a panel dataset, and I
do not understand the results and/or errors produced by the function, so I
want to be able to understand whether there is a problem with the structure
of my dataset, or I am not using the function properly or if there is
something else going on that I am ignoring. Also, I would like to know what
the start argument is for, or at least an example of how to use it, since I
don´t know how to properly apply it.
Here the details of what I am using and under what environment settings:
1-R version: 3.5.3
2-packages called: plm and pglm
3-Running on a 64-bit Operating System
4-Windows 8
Here is the code with the different things I have tried so far:
> PGLM_Model11 <-
pglm(dataframe3$TRANSIT~dataframe3$Draft+dataframe3$TOTALCOST+dataframe3$BUNKER+dataframe3$CHARTERVALUE,
effect=c("twoways"), model=c("random"), family=binomial('logit'),
index=c("ID","DATE"), start = NULL, data=dataframe3)
>
> summary(PGLM_Model11)
--------------------------------------------
Maximum Likelihood estimation
Newton-Raphson maximisation, 0 iterations
Return code 100: Initial value out of range.
--------------------------------------------
>
> PGLM_Model12 <-
pglm(dataframe3$TRANSIT~dataframe3$Draft+dataframe3$TOTALCOST+dataframe3$BUNKER+dataframe3$CHARTERVALUE,
effect=c("twoways"), model=c("pooling"), family=binomial('logit'),
index=c("ID","DATE"), start = NULL, data=dataframe3)
>
> summary(PGLM_Model12)
--------------------------------------------
Maximum Likelihood estimation
Newton-Raphson maximisation, 11 iterations
Return code 2: successive function values within tolerance limit
Log-Likelihood: -14.95426
5 free parameters
Estimates:
Estimate Std. error t value Pr(> t)
(Intercept) 93.9680425 Inf 0 1
dataframe3$Draft -5.3820652 Inf 0 1
dataframe3$TOTALCOST -0.0001689 Inf 0 1
dataframe3$BUNKER 0.0072934 Inf 0 1
dataframe3$CHARTERVALUE 0.0008862 Inf 0 1
--------------------------------------------
>
> PGLM_Model13 <-
pglm(dataframe3$TRANSIT~dataframe3$Draft+dataframe3$TOTALCOST+dataframe3$BUNKER+dataframe3$CHARTERVALUE,
effect=c("twoways"), model=c("within"), family=binomial('logit'),
index=c("ID","DATE"), start = NULL, data=dataframe3)
Error in maxRoutine(fn = logLik, grad = grad, hess = hess, start = start,
:
argument "start" is missing, with no default
>
> PGLM_Model14 <-
pglm(dataframe3$TRANSIT~dataframe3$Draft+dataframe3$TOTALCOST+dataframe3$BUNKER+dataframe3$CHARTERVALUE,
effect=c("twoways"), model=c("between"), family=binomial('logit'),
index=c("ID","DATE"), start = NULL, data=dataframe3)
Error in maxRoutine(fn = logLik, grad = grad, hess = hess, start = start,
:
argument "start" is missing, with no default
Below the dput of the dataset I am using for your reference:
> dput(dataframe3)
structure(list(TRANSIT = c(1L, 1L, 1L, 0L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 0L, 0L, 0L, 1L, 0L, 1L, 1L, 0L, 1L, 0L, 0L,
1L, 1L, 1L, 0L, 1L, 1L, 1L, 0L, 0L, 0L, 1L, 1L, 0L, 0L, 1L, 0L,
0L, 1L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 1L, 1L, 0L,
1L, 1L, 0L, 0L, 0L, 1L, 1L, 1L, 1L, 0L, 0L, 0L, 1L, 0L, 0L, 0L,
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1L, 1L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 1L, 1L, 0L, 1L, 1L,
0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 0L, 0L, 1L, 1L, 1L, 0L,
1L, 0L, 1L, 1L, 0L, 0L, 1L, 1L, 1L, 1L, 1L, 1L, 0L, 1L, 1L, 1L,
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1L, 0L, 1L, 0L, 0L, 1L, 1L, 0L, 0L, 1L, 1L, 1L, 0L, 1L, 0L, 0L,
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1L, 1L, 0L, 0L, 1L, 0L, 1L, 0L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L), ID = c(1L, 1L, 2L, 2L, 3L, 4L, 5L, 5L,
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90L, 91L, 92L, 93L, 93L, 94L, 95L, 96L, 97L, 98L, 99L, 100L,
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363L, 364L, 365L, 366L, 367L, 368L, 369L, 370L, 371L, 372L, 373L,
374L, 375L, 376L, 377L, 378L, 379L, 380L, 381L, 382L, 383L, 384L,
385L, 386L, 387L, 388L, 389L, 390L, 391L, 392L, 393L, 394L, 395L,
396L, 397L, 398L, 399L, 400L, 401L, 402L, 402L, 403L, 404L, 405L,
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427L, 428L, 429L, 430L, 431L, 432L, 433L, 434L, 434L, 435L, 436L,
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448L, 449L, 450L, 451L, 452L, 453L, 454L, 455L, 456L, 457L, 458L,
459L, 460L, 461L, 462L, 463L, 464L, 464L, 465L, 465L, 466L, 467L,
467L, 468L, 468L, 469L, 470L, 471L, 472L, 473L), DATE = structure(c(47L,
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"January 9 2018", "July 13 2018", "July 30 2017", "June 17 2018",
"June 8 2018", "March 10 2018", "March 13 2018", "March 18 2018",
"March 22 2018", "March 24 2018", "March 28 2018", "March 3 2018",
"November 1 2017", "November 10 2017", "November 11 2017", "November 12
2017",
"November 13 2017", "November 15 2017", "November 17 2017", "November 18
2017",
"November 19 2017", "November 21 2017", "November 22 2017", "November 23
2017",
"November 25 2017", "November 27 2017", "November 28 2017", "November 3
2017",
"November 4 2017", "November 5 2017", "November 6 2017", "November 7 2017",
"November 8 2017", "November 9 2017", "October 1 2017", "October 10 2017",
"October 11 2017", "October 12 2017", "October 14 2017", "October 15 2017",
"October 16 2017", "October 17 2017", "October 18 2017", "October 19 2017",
"October 20 2017", "October 21 2017", "October 23 2017", "October 25 2017",
"October 26 2017", "October 27 2017", "October 28 2017", "October 29 2017",
"October 3 2017", "October 30 2017", "October 31 2017", "October 4 2017",
"October 5 2017", "October 6 2017", "October 7 2017", "October 9 2017",
"September 1 2017", "September 10 2017", "September 11 2017",
"September 12 2017", "September 13 2017", "September 15 2017",
"September 16 2017", "September 17 2017", "September 19 2017",
"September 21 2017", "September 22 2017", "September 24 2017",
"September 26 2017", "September 27 2017", "September 29 2017",
"September 3 2017", "September 30 2017", "September 5 2017",
"September 6 2017", "September 7 2017", "September 8 2017", "September 9
2017"
), class = "factor"), SHIPNAME = structure(c(295L, 295L, 151L,
151L, 19L, 41L, 292L, 292L, 201L, 148L, 148L, 148L, 148L, 413L,
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297L, 297L, 118L, 279L, 230L, 230L, 340L, 358L, 473L, 271L, 309L,
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333L, 273L, 308L, 235L, 235L, 426L, 234L, 93L, 111L, 325L, 283L,
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349L, 4L, 226L, 465L, 362L, 128L, 264L, 136L, 50L, 18L, 323L,
11L, 11L, 25L, 408L, 302L, 180L, 394L, 113L, 434L, 477L, 461L,
305L, 174L, 104L, 152L, 132L, 291L, 410L, 250L, 382L, 351L, 23L,
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239L, 58L, 149L, 402L, 373L, 82L, 251L, 244L, 244L, 135L, 24L,
345L, 156L, 227L, 324L, 215L, 222L, 286L, 55L, 281L, 281L, 280L,
280L, 322L, 393L, 243L, 34L, 418L, 418L, 334L, 334L, 221L, 220L,
6L, 6L, 479L, 479L, 479L, 166L, 196L, 298L, 71L, 160L, 282L,
213L, 147L, 315L, 433L, 458L, 207L, 208L, 186L, 91L, 326L, 466L,
421L, 420L, 98L, 399L, 289L, 134L, 123L, 194L, 173L, 248L, 64L,
202L, 206L, 95L, 396L, 396L, 131L, 211L, 391L, 38L, 84L, 455L,
144L, 168L, 389L, 398L, 398L, 35L, 35L, 367L, 359L, 360L, 105L,
73L, 431L, 430L, 372L, 62L, 312L, 470L, 263L, 86L, 275L, 219L,
414L, 96L, 125L, 365L, 478L, 342L, 45L, 241L, 75L, 121L, 355L,
380L, 379L, 216L, 191L, 417L, 395L, 395L, 31L, 210L, 467L, 146L,
397L, 179L, 181L, 29L, 171L, 482L, 240L, 288L, 330L, 368L, 287L,
401L, 321L, 217L, 233L, 233L, 233L, 366L, 247L, 89L, 472L, 336L,
364L, 364L, 124L, 124L, 163L, 163L, 5L, 37L, 237L, 332L, 183L,
184L, 444L, 442L, 339L, 126L, 293L, 232L, 150L, 203L, 53L, 475L,
468L, 327L, 172L, 481L, 61L, 424L, 2L, 28L, 28L, 224L, 304L,
423L, 66L, 384L, 335L, 387L, 42L, 195L, 200L, 383L, 114L, 443L,
301L, 68L, 67L, 72L, 214L, 386L, 352L, 381L, 65L, 218L, 266L,
102L, 51L, 178L, 30L, 137L, 137L, 175L, 161L, 1L, 448L, 446L,
3L, 190L, 189L, 278L, 278L, 278L, 299L, 116L, 143L, 44L, 43L,
130L, 285L, 328L, 170L, 185L, 87L, 140L, 437L, 145L, 245L, 155L,
261L, 258L, 331L, 85L, 16L, 257L, 204L, 13L, 154L, 459L, 117L,
94L, 320L, 225L, 314L, 259L, 14L, 456L, 162L, 142L, 26L, 303L,
432L, 231L, 435L, 392L, 313L, 370L, 474L, 464L, 450L, 450L, 450L,
450L, 438L, 182L, 236L, 92L, 164L, 79L, 80L, 77L, 169L, 177L,
153L, 176L, 329L, 353L, 341L, 454L, 69L, 238L, 242L, 269L, 268L,
267L, 115L, 108L, 199L, 52L, 27L, 59L, 198L, 197L, 253L, 436L,
306L, 106L, 447L, 378L, 316L, 318L, 99L, 407L, 411L, 36L, 453L,
167L, 63L, 158L, 188L, 377L, 376L, 32L, 193L, 463L, 129L, 429L,
9L, 17L, 449L, 21L, 76L, 78L, 78L, 319L, 33L, 390L, 388L, 343L,
406L, 159L, 270L, 223L, 337L, 88L, 141L, 469L, 100L, 441L, 300L,
290L, 445L, 46L, 415L, 294L, 294L, 110L, 12L, 229L, 97L, 138L,
263L, 249L, 265L, 385L, 405L, 47L, 205L, 350L, 416L, 348L, 476L,
254L, 57L, 15L, 427L, 255L, 428L, 122L, 109L, 60L, 403L, 256L,
10L, 371L, 112L, 112L, 419L, 419L, 83L, 317L, 317L, 277L, 277L,
187L, 228L, 375L, 374L, 139L), .Label = c("Aby Jeannette", "Adelante",
"ADM Georgina", "ADS Galtesund", "Aeneas", "Aeolian Fortune",
"Aeolian Light", "AFRICA GRAECA", "AFRICAN ARROW", "AFRICAN BARI BIRD",
"AFRICAN BLUE CRANE", "AFRICAN FINFOOT", "AFRICAN JACANA", "AFRICAN KITE",
"AFRICAN LEOPARD", "AFRICAN PUFFIN", "AFRICAN RAPTOR", "AFTERHOURS",
"AGIA SKEPI", "Agri Kinsale", "Aiantas", "AKILI", "ALAM MANIS",
"ALBION", "Alexandra", "ALICIA", "Alma", "Alpha Vision", "AM BREMEN",
"AMAMI K", "AMIS ACE", "AMIS FORTUNE", "AMIS JUSTICE", "AMSTEL FALCON",
"Andros", "ANDROS ISLAND", "Androusa", "ANIMA", "Anna S", "Anna Smile",
"ANTIGONI", "Antiparos", "Aom Gaia", "AOM GAIA", "Aom Milena",
"APEX", "AREQUIPA QUEEN", "Ariana", "Artemis", "ASHIYA STAR",
"ASTRA CENTAURUS", "ASTREA", "Athina Carras", "ATLANTIC EAGLE",
"ATLANTIC GRACE", "ATLANTIC HERO", "ATLANTIC MANZANILLO", "Attalia",
"Axios", "Bahia Blanca", "Bali", "BALTIC K", "BALTIC WASP", "BBG Ambition",
"BBG Dream", "BBG Endeavor", "Belo Horizonte", "BELO HORIZONTE",
"BLUE AKIHABARA", "BLUE DIAMOND", "BLUE MARLIN I", "Bora", "Brasil SW",
"Braveheart", "BRIDGEGATE", "BRIGITTE", "BTG Denali", "BTG Eiger",
"BTG Everest", "BTG Kailach", "BULK ARGENTINA", "BULK COLOMBIA",
"BULK HERO", "BULK HONDURAS", "Bulk Pegasus", "Bulk Portugal",
"BW Hazel", "Captain Adams", "Captain Antonis", "Cemtex Wisdom",
"CENTENARIO BLU", "Cepheus Ocean", "Cerafina", "Cetus Ocean",
"CF Diamond", "CHARADE", "CHLOE", "CLARKE QUAY", "CLIPPER AMSTERDAM",
"Clipper Victory", "CMB Sakura", "Cofco 1", "COLUMBIA RIVER",
"Coral Diamond", "COREFORTUNE OL", "Cosmar", "Coventry", "CP GUANGZHOU",
"Crimson Ark", "Crimson Kingdom", "Cymona Star", "DALIAN STAR",
"De Xu Hai", "Densa Pelican", "DESERT CHALLENGER", "DEVON BAY",
"DIAMOND QUEEN", "Dias", "Dimitris Apesakis", "Donousa", "DORIC",
"DORIC SHOGUN", "DORO", "EASTER N", "Efrain A", "Egret Oasis",
"Eirini P", "Elena", "Emerald Dongji", "Emerald Star", "ENDLESS HORIZON",
"ENY", "Erikoussa", "ESSEX STRAIT", "Eternal Bliss", "Eternal Grace",
"EUROPA BAY", "Ever Grace", "EVER SOVEREIGN", "Everglory", "Evmar",
"FEDERAL TRIDENT", "FH Fang Cheng", "FH Rizhao", "Fiji", "FILIA JOY",
"Flag Lama", "FLIPPER", "FLORINDA", "Fortune Harmony", "FORTUNE LADY",
"FORTUNE UNITY", "FRAMURA", "FURNESS VICTORIA", "Galio", "GANNET BULKER",
"GENCO RAPTOR", "GH CITATION", "GH URBAN SEA", "Giorgakis", "Giorgis",
"GLOBAL PRIME", "GLOBAL SUCCESS", "GLOBAL VISION", "Glory", "Golden Jake",
"GOLDEN LIBRA", "Good Wish", "Graecia Aeterna", "GRAND CONCORD",
"GRAND MARCIA", "Great Rich", "GUARDIANSHIP", "Hampton Bay",
"Hampton Bridge", "HANTON TRADER I", "Hercules Ocean", "Hermes",
"Hong Hing", "Hong Jing", "Hong Sheng", "HOPA I", "Huayang Spirit",
"Huayeng Dream", "Indian Harmony", "INDIGO EVOLUTION", "INDIGO RIVER",
"INDRA OLDENDORFF", "Innovation", "INNOVATION", "Inspiration",
"IRIS HALO", "IRIS OLDENDORFF", "ISMENE", "Istria", "IYO WIND",
"Jag Aalok", "Jag Akshay", "Jag Arnav", "JIA SHENG SHAN", "JIN RUN",
"Jin Zhu Hai", "John M. Carras", "JOSCO HANGZHOU", "JPS AFRODITI",
"K SPINEL", "K. GARNET", "K. OPAL", "KANG CHENG", "Karlovasi",
"Katerina III", "KAVO PALOMA", "Kea", "Kerkyra", "Key Evolution",
"Key Pacifico", "KING ISLAND", "KING MILO", "KM Fukuyama", "KM Hong Kong",
"KM Keelung", "KM Yokohama", "KMARIN SINGAPORE", "KT Birdie",
"KYRA PANAGHIA", "Lady I", "LEO ADVANCE", "LESEDI QUEEN", "LILA",
"LISSA TOPIC", "LOCH SHUNA", "Long Dar", "LOUISIANA MAMA", "LOWLANDS
MAINE",
"LUMINOUS HALO", "LUNITA", "LYRIC HARMONY", "Macheras", "MALMO",
"MANDARIN CROWN", "MANDARIN NOBLE", "Marathassa", "MARIE GRACE",
"MARINER", "MARITIME PROSPERITY", "MARY LINA", "Mastro Nikos",
"MBA Future", "Medi Matsuura", "MEDI SALERNO", "MELBOURNE", "MELIA",
"METSOVO", "MG Explorer", "MG Kronos", "MG Sakura", "Miao Xiang",
"MISATO K", "Mistral I", "Miyama", "Mykonos", "Myra", "Myrto",
"N Bonanza", "Nadeshiko", "Naias", "NAUTICAL MARIE", "NAUTICAL RUNA",
"NAUTICAL SIF", "Navios Amber", "NAVIOS ARC", "NAVIOS ARMONIA",
"Navios Harmony", "Navios Orbiter", "NAVIOS SOUTHERN STAR", "NEFELI",
"NEW BLISS", "NEW DIRECTION", "NEWSEAS PEARL", "NIKKEI SIRIUS",
"NIKKEI VERDE", "Nikolaos", "NIKOLAS XL", "Nikomarin", "Nord Capella",
"Nord Fortune", "NOSHIMA", "Nuri Bey", "OCCITAN PAUILLAC", "OCEAN BAO",
"OCEAN BELT", "OCEAN FAVOUR", "Ocean Garlic", "OCEAN HARVEST",
"OCEAN PRIDE", "OCEAN PRINCE", "OCEAN PRINCESS", "OCEAN ROYAL",
"OCEAN SPLENDOR", "OCEAN TIANBAO", "OCEAN VENUS", "Ocean Wind",
"Oceana", "Odysseas L", "OKINAWA", "Olivia R", "OLYMPOS", "Omicron Light",
"OMICRON NIKOS", "OMICRON SKY", "Omicron Trader", "ORCHID HALO",
"Orient Genesis", "ORIENT GRACE", "OZGUR AKSOY", "PACIFIC ADVANCE",
"PACIFIC NEXUS", "PACIFIC TALENT", "PACIFIC VICTORY", "Palais",
"Pan Ceres", "PAN VIVA", "Panafrican", "Panamanian", "Panasiatic",
"PANORIA", "Panther Max", "PARADISE ISLAND", "PAUL OLDENDORFF",
"Peace Ark", "PEAK PEGASUS", "Pedhoulas Farmer", "Pedhoulas Trader",
"PENTA", "PERIDOT", "PERTH I", "Phaedra", "PHOENIX K", "Phoenix Ocean",
"Pictor", "PILATUS VENTURE", "Popi S", "PORT ESTRELA", "Proteas",
"QUEEN JHANSI", "QUEEN KOBE", "Rave", "RB Eden", "Real Happiness",
"RECCO", "REGAL", "RESURGENCE", "RIGI VENTURE", "Rosalia D´ Amato",
"Rosco Banyan", "Rosco Cypress", "Rosco Ginkgo", "Rosco Lemon",
"Rosco Litchi", "Rosco Palm", "ROSCO PLUM", "Rosco Poplar", "Rosco
Sandalwood",
"RR Australia", "SAGAR JYOTI", "SAGAR SHAKTI", "SAGARJEET", "SAGE
COLORADO",
"SAGE PIONEER", "SAILING SKY", "Sakizaya Power", "SAN ANTONIO",
"SANTA KATARINA", "SANTA VALENTINA", "SANYU", "SBI Bolero", "SBI BOLERO",
"SBI Samba", "Scarlet Cardinal", "SCARLET CARDINAL", "Scarlet Falcon",
"Sea Duty", "Sea Hermes", "Sea Pegasus", "SEA PIONEER", "Sea Pluto",
"Seatribute", "Shandong Fu Hui", "Shandong Hai Chang", "Shangdong Fu Ze",
"Shao Shan 5", "Shao Shan 8", "SIFNOS", "Silver Dragon", "SIMURGH",
"Skiathos", "SKY KNIGHT", "SONGA GLORY", "SOUTHEND", "SPARNA",
"SPRING AEOLIAN", "SPRING EAGLE", "SPRING ZEPHYR", "SSI CHALLENGER",
"Stalo", "STAMFORD EAGLE", "STAR AQUARIUS", "STAR JENNIFER",
"Star Laura", "Star of Sawara", "STAR PISCES", "Star Renee",
"STAR VANESSA", "STARRY SKY", "STH LONDON", "STOVE FRIEND", "STOVE OCEAN",
"SUNLEAF GRACE", "SUNLEAF STAR", "SUNNY HOPE", "SUNNY ROYAL",
"SUZAKU", "Syros I", "Tahiti One", "Tai Promotion", "TAI PROSPERITY",
"TAI SPRING", "TAI STAR", "TAI SUMMIT", "Tangerine Island", "TANGERINE
ISLAND",
"TANIKAZE", "TASSOS N", "Taurus Ocean", "TEAL BULKER", "TENRO MARU",
"Tenten", "THEMISTOCLES", "Theodor Oldendorff", "THEODOR OLDENDORFF",
"Theodore Jr.", "Theresa Hebei", "Theresa Jilin", "Theresa Shandong",
"TIGER HENAN", "TIGER NORTH", "TIGER PIONEER", "Tiger South",
"TN SUNRISE", "TOMORROW", "Topaz", "TORENIA", "TR Lady", "Trade Unity",
"TRANS OCEANIC", "TRUSTN TRADER II", "TSCHAIKOWSKY", "TTM DRAGON",
"Tuo Fu 6", "Tycoon", "ULTRA PANTHER", "Unity", "UNITY DISCOVERY",
"Valadon", "VEGA ROSE", "VELA OCEAN", "VENUS", "VENUS HALO",
"VICTORIA", "VISHVA ANAND", "Vitahorizon", "Vitakosmos", "Vivian",
"VSC CASTOR", "VSC TRITON", "XING XI HAI", "Yarrawonga", "Yue Guan Feng",
"ZEN-NOH GRAIN MAGNOLIA", "ZEN-NOH GRAIN PEGASUS", "Zheng Zhi",
"Zhi He"), class = "factor"), Draft = c(12L, 12L, 12L, 13L, 12L,
12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 14L, 14L, 14L, 12L,
13L, 12L, 12L, 14L, 12L, 14L, 13L, 12L, 12L, 12L, 14L, 12L, 12L,
11L, 13L, 13L, 14L, 12L, 12L, 13L, 14L, 12L, 13L, 13L, 12L, 14L,
14L, 13L, 12L, 14L, 14L, 13L, 14L, 14L, 12L, 13L, 12L, 12L, 13L,
12L, 12L, 14L, 14L, 14L, 12L, 12L, 12L, 12L, 14L, 13L, 14L, 12L,
13L, 14L, 13L, 12L, 12L, 12L, 12L, 12L, 12L, 14L, 12L, 14L, 13L,
14L, 14L, 12L, 12L, 12L, 14L, 12L, 12L, 13L, 14L, 13L, 13L, 12L,
14L, 13L, 13L, 14L, 12L, 12L, 14L, 12L, 12L, 14L, 12L, 13L, 13L,
14L, 14L, 14L, 14L, 12L, 12L, 14L, 13L, 12L, 12L, 12L, 13L, 12L,
14L, 12L, 12L, 14L, 14L, 12L, 12L, 12L, 12L, 12L, 12L, 13L, 12L,
12L, 12L, 13L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 14L, 12L, 12L,
12L, 12L, 14L, 14L, 14L, 14L, 10L, 12L, 11L, 12L, 12L, 12L, 12L,
12L, 12L, 12L, 12L, 12L, 12L, 13L, 14L, 14L, 14L, 12L, 12L, 12L,
14L, 12L, 12L, 12L, 14L, 14L, 14L, 14L, 12L, 12L, 11L, 12L, 12L,
12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 10L, 12L, 12L, 12L, 11L,
13L, 14L, 14L, 12L, 13L, 14L, 14L, 12L, 13L, 14L, 12L, 12L, 12L,
14L, 13L, 14L, 12L, 12L, 14L, 14L, 12L, 14L, 13L, 12L, 14L, 12L,
14L, 12L, 12L, 12L, 12L, 14L, 13L, 12L, 13L, 12L, 12L, 14L, 12L,
14L, 14L, 14L, 12L, 12L, 12L, 13L, 12L, 14L, 14L, 14L, 12L, 12L,
12L, 12L, 13L, 12L, 12L, 12L, 14L, 14L, 12L, 12L, 14L, 12L, 14L,
14L, 12L, 12L, 12L, 13L, 12L, 12L, 12L, 12L, 12L, 14L, 14L, 13L,
12L, 13L, 14L, 12L, 12L, 12L, 12L, 13L, 14L, 12L, 14L, 13L, 14L,
14L, 14L, 14L, 14L, 13L, 14L, 14L, 13L, 14L, 12L, 12L, 14L, 14L,
14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 14L, 13L, 12L, 14L,
14L, 14L, 12L, 14L, 14L, 14L, 12L, 12L, 14L, 14L, 14L, 14L, 12L,
14L, 14L, 12L, 14L, 14L, 12L, 13L, 12L, 12L, 12L, 14L, 14L, 13L,
14L, 12L, 13L, 13L, 13L, 12L, 12L, 12L, 12L, 12L, 14L, 12L, 14L,
13L, 14L, 12L, 12L, 14L, 13L, 14L, 14L, 14L, 12L, 14L, 14L, 12L,
12L, 14L, 12L, 14L, 12L, 12L, 12L, 14L, 12L, 13L, 14L, 12L, 12L,
14L, 12L, 12L, 12L, 12L, 12L, 14L, 12L, 12L, 12L, 14L, 14L, 12L,
12L, 14L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 14L, 12L, 13L, 13L,
13L, 14L, 14L, 12L, 12L, 12L, 12L, 12L, 13L, 12L, 14L, 13L, 12L,
12L, 12L, 12L, 12L, 13L, 12L, 14L, 13L, 13L, 13L, 11L, 12L, 14L,
14L, 12L, 14L, 12L, 11L, 12L, 12L, 12L, 12L, 14L, 12L, 12L, 12L,
12L, 14L, 14L, 12L, 12L, 12L, 14L, 12L, 12L, 12L, 12L, 14L, 12L,
13L, 14L, 12L, 12L, 14L, 14L, 12L, 12L, 12L, 13L, 12L, 14L, 14L,
14L, 12L, 14L, 13L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 13L, 6L,
12L, 12L, 14L, 14L, 14L, 14L, 12L, 14L, 12L, 12L, 12L, 12L, 14L,
12L, 14L, 12L, 12L, 12L, 14L, 12L, 12L, 13L, 14L, 12L, 13L, 12L,
14L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L,
12L, 12L), TOTALCOST = c(194364L, 219364L, 198260L, 237456L,
197159L, 198992L, 194337L, 219337L, 199198L, 196604L, 230607L,
196604L, 196604L, 194496L, 238600L, 236936L, 237476L, 197220L,
236950L, 197300L, 182042L, 237938L, 199221L, 237475L, 239190L,
157406L, 157211L, 182211L, 237475L, 182475L, 181599L, 156599L,
238269L, 238402L, 238069L, 161436L, 225031L, 238180L, 237572L,
189861L, 239005L, 239049L, 163814L, 240064L, 239171L, 238410L,
200878L, 239019L, 239087L, 239350L, 239352L, 240275L, 164844L,
238400L, 225158L, 202495L, 239681L, 201791L, 226863L, 244092L,
244590L, 239171L, 189811L, 219412L, 228480L, 203650L, 237514L,
247451L, 244739L, 211770L, 244308L, 239197L, 238419L, 224977L,
157362L, 162434L, 162434L, 162434L, 162434L, 239681L, 163316L,
237265L, 243920L, 244088L, 244163L, 202256L, 159592L, 201346L,
239187L, 189800L, 191959L, 239476L, 239171L, 238087L, 238052L,
164169L, 245057L, 244215L, 240812L, 239156L, 156879L, 197853L,
245367L, 164710L, 164710L, 244192L, 211110L, 239156L, 244213L,
237504L, 239018L, 241150L, 244447L, 238506L, 210298L, 243482L,
239166L, 159489L, 184600L, 226439L, 239127L, 235243L, 244296L,
159696L, 189046L, 244355L, 244446L, 187595L, 162595L, 162595L,
162595L, 170604L, 188774L, 244103L, 188680L, 163611L, 200551L,
244055L, 170606L, 169154L, 194154L, 170905L, 200551L, 191412L,
166412L, 243969L, 170483L, 210719L, 168554L, 164016L, 245158L,
245131L, 245186L, 239166L, 116360L, 155698L, 155698L, 155698L,
155698L, 223827L, 191968L, 159650L, 189999L, 201193L, 201011L,
226218L, 201218L, 243970L, 244291L, 243993L, 243993L, 236035L,
236035L, 236035L, 244070L, 159692L, 194183L, 169110L, 241994L,
238216L, 238301L, 242948L, 169810L, 189280L, 164662L, 164156L,
189156L, 163989L, 163924L, 159577L, 159650L, 170566L, 170598L,
188975L, 189006L, 99983L, 191595L, 166907L, 228744L, 166621L,
243593L, 244001L, 239035L, 172934L, 238288L, 241665L, 241665L,
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-527L))
Any help and/or guidance will be greatly appreciated,
Best regards,
Paul
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