Линейная регрессия lm с несколькими манекенами при ограничениях в R
Я пытаюсь выполнить регрессию с несколькими манекенами с некоторыми ограничениями. Формула будет выглядеть так: Возврат ~ Страна + Сектор при ограничении суммы беты для страны, равной 0, и такой же для сектора. Код выглядит следующим образом: (dput для воспроизведения данных внизу)
test = lm(Ret ~ Dum.count + Dum.sect + 0 , data=reg.data, weights = weight)
Проблема в том, что
test$coefficients
Не отображаются все коэффициенты (он забывает сектор "потребительский усмотрение"). Я читал, что фиктивная модель в R добровольно опускает одну манекен для использования в качестве перехвата, поэтому я использовал 0 в формуле.
Что касается ограничений, я думал об использовании
options(contrasts=c('contr.sum', 'contr.sum'))
Что должно обеспечить некоторые из бета-версии до 0, хотя я думаю, что по умолчанию R применяет такое ограничение к фиктивным регрессиям.
Мой вопрос прост: как мне получить коэффициент для всех фиктивных переменных, а также перехват в Ret ~ Dum.Count + Dum.sect.
Данные:
structure(list(Ret = c(0, 0, -0.029207812448361, -0.0130948776039107,
0, -0.0139720566633232, -0.0101638349799049, -0.014567900868859,
-0.0160237311029044, 0, -0.0138193495631563, -0.0118883623673851,
-0.0127607940998118, -0.0168323947578526, -0.0140598414299611,
-0.0270653026036032, -0.013511069247101, -0.0190114076115796,
-0.00954127690170647, -0.00814207809427425, -0.0158862534893693,
0.00250062313018495, -0.015424574198733, -0.0171911400649766,
-0.0161667102628111, 0.0475020485164568, 0, 0, 0, -0.00777133018019516,
-0.0157298360407402, 0.0053586713804914, 0.0179304441180137,
0.00979384741520195, 0.0116018269502725, 0.00122347981174808,
0.0115073954888256, 0.00775992307966877, 0.0121949267497194,
-0.0146997128177213, -0.000215525277190709, -0.00896361197372919,
-0.000835923344706724, -0.000232890994861901, 0.00641661895030676,
-0.0104823974697706, -0.00844271241021, -0.00432712125533785,
-0.00960478935057751, 0, 0, 0, 0, 0, 0, 0, 0, 0.00506636768628788,
0.0097798264183806, 0.0143961770922494, 0.0252683812565806, 0.00563260340433058,
0.00334287848464543, 0.00835714828430389, 0.0107771256263582,
-0.00696322657200987, -0.0214181284389567, -0.0116731306341926,
-0.0140633511378349, -0.00194417471772934, -0.0177431321483384,
-0.0142454788364048, -0.0030061504164367, -0.00985741567595944,
0.00792966751267032, -0.0157232672422116, 0.00125884611876703,
0.0310231057254129, 0.00402193467607681, -0.00121009036148767,
0.00022232060186167, 0.0484403657127666, -0.0102214651737076,
-0.0249988098851416, -0.0216788100661882, -0.0137027808902404,
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-0.0176606200709191, -0.00184024399175853, -0.0359503321252187,
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-0.00280373699740988, -0.0243112060592608, -0.0132383744206145,
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0.0153246731111047, 0.00245398972794453, 0, 0, 0, 0, 0, 0, 0,
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-0.0176723497534155, -0.0141871872888074, -0.00517469051101072,
-0.0206752390244536, -0.0159270507413398, -0.0162002498088399,
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0.00890911631628999, 0.00857579687603893, -0.000430800128892739,
-0.00148239510920689, 0.0177863306273693, 0.0044396555126669,
0.00229617979641938, -0.0227630449473507, 0.0074472075431038,
0.0125810156721518, 0, 0, 0, -0.00548986480087421, -0.0154140902995596,
-0.0068965480035369, 0, -0.00100669807072151, 0.00581395503714099,
-0.00962155191477765, -0.00467889485209072, -0.00503685129724607,
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0.00851811791112023, 0.00254171513696044, -0.00791855191519375,
-0.00307692209748389, 0.00415078078716569, 0.0133393358554736,
0.00516195600887026, 0, 0, 0, 0, 0, 0, 0.00208014929305977, 0.00785231023761823,
-0.0098290573835752, -0.0376134812621233, 0.0180416603872335,
0.00679611592663321, 0.00824431937901626, -0.0162141805546233,
0.0212896626455286, -0.0988173014048515, -0.0242649161941374,
0, 0, 0, 0, -0.00100339644936687, -0.00542904187899385, 0.00762711896673074,
-0.00274629483394417, 0.00639258109944429, -0.0253452486656157,
-0.0234059631154547, -0.0106856645844248, -0.0105048879803891,
-0.00996965670698602, -0.00994173530622566, -0.00417057735172199,
-0.0181977597109311, -0.00903209483385536, -0.0110172402005969,
-0.00708584774262722, -0.00188880873871866, -0.00214252049768071,
-0.0106430227519835, -0.0143493081253891, -0.00838724216786557,
-0.00105298694133393, 0.00508702582645171, -0.0168949074416769,
0.0064401025366938, 0.0213990855365818, 0.0038106323595648, -0.00195721095748969,
0.0147058822269497, 0.0066857684565933, 0.00186540579163852,
-0.00726165400197554, -0.0119383516086875, -0.0164804096531268,
0.00324923087488393, 0.00309000870142828, 0, -0.00738244417262734,
0.00353081443803238, -0.0114724575309201, 0.000107350663112404,
-0.00552486283201059, -0.0152003926399522, -0.00202485399514052,
0.00494151428543499, -0.00760244020239975, 0.000151309270926658,
-0.000995887251685423, -0.00340575234330787, 0.00794552468230658,
-0.000254961250433228, -0.00849117013431566, -0.00357495164666255,
-0.00868093244254886, 0.00454884652721699, -0.0102508862917655,
-0.00724354855628362, -0.0203438713533814, 0.00047778086527539,
-0.00191240348648059, -0.00148113348601808, -0.00141339061818291,
-0.00944409014293923), Dum.sect = c("Industrials", "Financials",
"Energy", "Financials", "Telecom Services", "Energy", "Materials",
"Industrials", "Financials", "Telecom Services", "Energy", "Materials",
"Industrials", "Consumer Discretionary", "Consumer Staples",
"Health Care", "Financials", "Information Technology", "Telecom Services",
"Utilities", "Materials", "Consumer Discretionary", "Consumer Staples",
"Health Care", "Financials", "Telecom Services", "Materials",
"Financials", "Telecom Services", "Energy", "Materials", "Industrials",
"Consumer Discretionary", "Consumer Staples", "Health Care",
"Financials", "Information Technology", "Telecom Services", "Utilities",
"Energy", "Materials", "Industrials", "Consumer Discretionary",
"Consumer Staples", "Health Care", "Financials", "Information Technology",
"Telecom Services", "Utilities", "Energy", "Materials", "Industrials",
"Consumer Discretionary", "Consumer Staples", "Health Care",
"Financials", "Telecom Services", "Energy", "Materials", "Industrials",
"Consumer Discretionary", "Consumer Staples", "Financials", "Telecom Services",
"Utilities", "Energy", "Materials", "Industrials", "Consumer Discretionary",
"Consumer Staples", "Health Care", "Financials", "Information Technology",
"Telecom Services", "Utilities", "Energy", "Materials", "Consumer Staples",
"Financials", "Utilities", "Financials", "Telecom Services",
"Utilities", "Materials", "Industrials", "Consumer Discretionary",
"Consumer Staples", "Health Care", "Financials", "Information Technology",
"Telecom Services", "Utilities", "Materials", "Industrials",
"Consumer Discretionary", "Consumer Staples", "Health Care",
"Financials", "Telecom Services", "Financials", "Telecom Services",
"Energy", "Industrials", "Consumer Discretionary", "Consumer Staples",
"Health Care", "Financials", "Information Technology", "Telecom Services",
"Utilities", "Energy", "Materials", "Industrials", "Consumer Discretionary",
"Health Care", "Financials", "Information Technology", "Telecom Services",
"Utilities", "Energy", "Materials", "Industrials", "Consumer Discretionary",
"Consumer Staples", "Health Care", "Financials", "Information Technology",
"Telecom Services", "Utilities", "Energy", "Materials", "Industrials",
"Consumer Discretionary", "Consumer Staples", "Health Care",
"Financials", "Information Technology", "Telecom Services", "Utilities",
"Materials", "Consumer Discretionary", "Financials", "Telecom Services",
"Utilities", "Industrials", "Consumer Discretionary", "Financials",
"Information Technology", "Telecom Services", "Utilities", "Energy",
"Health Care", "Financials", "Energy", "Materials", "Industrials",
"Consumer Discretionary", "Consumer Staples", "Health Care",
"Financials", "Telecom Services", "Utilities", "Materials", "Industrials",
"Consumer Staples", "Financials", "Energy", "Materials", "Health Care",
"Financials", "Information Technology", "Telecom Services", "Energy",
"Materials", "Industrials", "Consumer Discretionary", "Consumer Staples",
"Health Care", "Financials", "Information Technology", "Telecom Services",
"Utilities", "Energy", "Industrials", "Consumer Discretionary",
"Financials", "Telecom Services", "Utilities", "Materials", "Financials",
"Telecom Services", "Energy", "Materials", "Industrials", "Consumer Discretionary",
"Consumer Staples", "Health Care", "Financials", "Information Technology",
"Telecom Services", "Utilities", "Energy", "Materials", "Industrials",
"Consumer Discretionary", "Consumer Staples", "Health Care",
"Financials", "Information Technology", "Telecom Services", "Utilities",
"Industrials", "Financials", "Telecom Services", "Industrials",
"Consumer Staples", "Financials", "Materials", "Financials",
"Telecom Services", "Telecom Services", "Energy", "Materials",
"Industrials", "Consumer Discretionary", "Consumer Staples",
"Health Care", "Financials", "Telecom Services", "Utilities",
"Energy", "Materials", "Industrials", "Consumer Discretionary",
"Consumer Staples", "Financials", "Information Technology", "Telecom Services",
"Energy", "Materials", "Consumer Staples", "Financials", "Telecom Services",
"Materials", "Industrials", "Health Care", "Information Technology",
"Telecom Services", "Utilities", "Materials", "Financials", "Telecom Services",
"Materials", "Financials", "Industrials", "Consumer Discretionary",
"Consumer Staples", "Financials", "Telecom Services", "Utilities",
"Energy", "Materials", "Consumer Staples", "Financials", "Telecom Services",
"Utilities", "Energy", "Materials", "Consumer Discretionary",
"Consumer Staples", "Financials", "Telecom Services", "Utilities",
"Energy", "Consumer Staples", "Financials", "Utilities", "Industrials",
"Financials", "Telecom Services", "Utilities", "Energy", "Materials",
"Consumer Staples", "Financials", "Telecom Services", "Utilities",
"Energy", "Materials", "Industrials", "Consumer Discretionary",
"Consumer Staples", "Health Care", "Financials", "Information Technology",
"Telecom Services", "Industrials", "Consumer Discretionary",
"Consumer Staples", "Financials", "Telecom Services", "Energy",
"Materials", "Industrials", "Consumer Discretionary", "Consumer Staples",
"Health Care", "Financials", "Telecom Services", "Utilities",
"Energy", "Materials", "Industrials", "Consumer Discretionary",
"Consumer Staples", "Financials", "Telecom Services", "Energy",
"Materials", "Industrials", "Consumer Discretionary", "Consumer Staples",
"Health Care", "Financials", "Information Technology", "Telecom Services",
"Energy", "Materials", "Industrials", "Consumer Discretionary",
"Consumer Staples", "Health Care", "Financials", "Information Technology",
"Telecom Services", "Utilities", "Energy", "Materials", "Industrials",
"Consumer Discretionary", "Consumer Staples", "Health Care",
"Financials", "Telecom Services"), Dum.count = structure(c(79L,
79L, 3L, 3L, 3L, 5L, 5L, 5L, 5L, 5L, 4L, 4L, 4L, 4L, 4L, 4L,
4L, 4L, 4L, 4L, 8L, 8L, 8L, 8L, 8L, 8L, 6L, 6L, 6L, 11L, 11L,
11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 14L, 14L, 14L, 14L, 14L,
14L, 14L, 14L, 14L, 14L, 73L, 73L, 73L, 73L, 73L, 73L, 73L, 73L,
15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 16L, 16L, 16L, 16L, 16L,
16L, 16L, 16L, 16L, 16L, 17L, 17L, 17L, 17L, 17L, 20L, 20L, 20L,
30L, 30L, 30L, 30L, 30L, 30L, 30L, 30L, 30L, 21L, 21L, 21L, 21L,
21L, 21L, 21L, 23L, 23L, 70L, 70L, 70L, 70L, 70L, 70L, 70L, 70L,
70L, 27L, 27L, 27L, 27L, 27L, 27L, 27L, 27L, 27L, 29L, 29L, 29L,
29L, 29L, 29L, 29L, 29L, 29L, 29L, 12L, 12L, 12L, 12L, 12L, 12L,
12L, 12L, 12L, 12L, 32L, 32L, 32L, 32L, 32L, 33L, 33L, 33L, 33L,
33L, 33L, 34L, 34L, 34L, 36L, 36L, 36L, 36L, 36L, 36L, 36L, 36L,
36L, 37L, 37L, 37L, 37L, 38L, 38L, 38L, 38L, 38L, 38L, 35L, 35L,
35L, 35L, 35L, 35L, 35L, 35L, 35L, 35L, 39L, 39L, 39L, 39L, 39L,
39L, 42L, 42L, 42L, 41L, 41L, 41L, 41L, 41L, 41L, 41L, 41L, 41L,
41L, 69L, 69L, 69L, 69L, 69L, 69L, 69L, 69L, 69L, 69L, 45L, 45L,
45L, 71L, 71L, 71L, 51L, 51L, 51L, 50L, 48L, 48L, 48L, 48L, 48L,
48L, 48L, 48L, 48L, 52L, 52L, 52L, 52L, 52L, 52L, 52L, 52L, 55L,
55L, 55L, 55L, 55L, 53L, 53L, 53L, 53L, 53L, 53L, 56L, 56L, 56L,
58L, 58L, 59L, 59L, 59L, 59L, 59L, 59L, 57L, 57L, 57L, 57L, 57L,
57L, 60L, 60L, 60L, 60L, 60L, 60L, 60L, 61L, 61L, 61L, 61L, 62L,
62L, 62L, 62L, 64L, 64L, 64L, 64L, 64L, 64L, 72L, 72L, 72L, 72L,
72L, 72L, 72L, 72L, 72L, 66L, 66L, 66L, 66L, 66L, 75L, 75L, 75L,
75L, 75L, 75L, 75L, 75L, 75L, 78L, 78L, 78L, 78L, 78L, 78L, 78L,
74L, 74L, 74L, 74L, 74L, 74L, 74L, 74L, 74L, 81L, 81L, 81L, 81L,
81L, 81L, 81L, 81L, 81L, 81L, 68L, 68L, 68L, 68L, 68L, 68L, 68L,
68L), .Label = c("ACWI", "ACWI + FM", "ARGENTINA", "AUSTRALIA",
"AUSTRIA", "BAHRAIN", "BANGLADESH", "BELGIUM", "BOSNIA-HERZE.",
"BOTSWANA", "BRAZIL", "BRITAIN", "BULGARIA", "CANADA", "CHILE",
"CHINA", "COLOMBIA", "COSTA RICA", "CROATIA", "CZECH", "DENMARK",
"Dev.", "EGYPT", "EM", "ESTONIA", "EUROZONE", "FINLAND", "FM",
"FRANCE", "GERMANY", "GHANA", "GREECE", "HONG KONG", "HUNGARY",
"INDIA", "INDONESIA", "IRELAND", "ISRAEL", "ITALY", "JAMAICA",
"JAPAN", "JORDAN", "KAZAKHSTAN", "KENYA", "KUWAIT", "LEBANON",
"LITHUANIA", "MALAYSIA", "MAURITIUS", "MEXICO", "MOROCCO", "NETHERLANDS",
"NEW ZEALAND", "NIGERIA", "NORWAY", "OMAN", "PAKISTAN", "PERU",
"PHILIPPINES", "POLAND", "PORTUGAL", "QATAR", "ROMANIA", "RUSSIA",
"Serbia", "SINGAPORE", "SLOVENIA", "SOUTH AFRICA", "SOUTH KOREA",
"SPAIN", "SRI LANKA", "SWEDEN", "SWITZERLAND", "TAIWAN", "THAILAND",
"TRINIDAD", "TUNISIA", "TURKEY", "UAE", "UKRAINE", "UNITED STATES",
"VIETNAM", "ZIMBABWE"), class = "factor"), weight = c(NA, 0.000520041385521202,
9.01950553319875e-05, 0.000100591224348651, 5.41621580434692e-05,
0.000167148878114065, 0.000140032197917218, NA, 0.00043289861233755,
3.03216418923979e-05, 0.0017041844684895, 0.00558849753044759,
NA, 0.000532655412075508, 0.00282636184938851, 0.00128555299047677,
0.0158196948568543, 0.000162084131914362, 0.00066973539869799,
0.000442374807565757, 0.0004169308466344, 7.98731009207813e-05,
0.00274454423202768, 0.000292217898089771, 0.000833908749188782,
0.000148992698676594, 5.37002442822141e-06, 2.55035767874359e-05,
1.13844215503653e-05, 0.00197425770290485, 0.00185089458809941,
NA, 0.00073674898431422, 0.00203490652583355, 9.56794065099678e-05,
0.00424438201363887, 0.000437306245555718, 0.000353266337830866,
0.000677331306890789, 0.0109142635212147, 0.00482170736142478,
NA, 0.00212241054424136, 0.00125334951768297, 0.00134049492981561,
0.0154267153937078, 0.000542182688412873, 0.000995453476412365,
0.000489874175993142, 0.000417456462489544, 0.00225274622367484,
NA, 0.00204031743017601, 0.00748408941402412, 0.01238330940116,
0.00606523455844243, 0.000370800808101754, 0.000159812550668776,
0.000187214745647669, NA, 0.000225733316656032, 0.0002152444548593,
0.000301865173738152, 4.12098919897373e-05, 0.000474066528275033,
0.00313691335134659, 0.000654393929077847, NA, 0.00121581726238987,
0.001197014138175, 0.00038575577333429, 0.00845368851837658,
0.00306158774774048, 0.00243686572288116, 0.000892091475960867,
0.000235494113417541, 0.000258004167635095, 9.59520022496746e-05,
0.000526395755998036, 9.49184607846087e-05, 9.46872741803485e-05,
3.12084980957958e-05, 0.00012980482830891, 0.00476274175547434,
NA, 0.00708771065718882, 0.00129721800667729, 0.00451975766039623,
0.00565243144711742, 0.00252204805736615, 0.00150427736450649,
0.00158669914655263, 0.000328481525529262, NA, 0.000223199361310245,
0.000293105007098944, 0.00289127372344326, 0.000596892251968017,
0.000237504201989964, 0.000182415912144681, 7.23719371526633e-05,
0.000621123627831815, NA, 0.000893240221040478, 0.000145324872475037,
0.000191033269383196, 0.00672776172771586, 0.000423632069828311,
0.00189383338550945, 0.00184917767521366, 6.77939415842332e-05,
0.000384070454868823, NA, 0.000112755275328428, 0.000105370182886625,
0.000629423497685844, 0.00083818255773377, 0.000114319753545826,
0.000320949927350397, 0.00420435515895106, 0.00223772646545699,
NA, 0.00504666689511999, 0.00384833173975654, 0.00416684718091077,
0.00636221222504172, 0.00113088254061143, 0.00186618128466519,
0.00161475781397291, 0.0143614055727104, 0.00802003670008823,
NA, 0.00647120211531932, 0.0132138727218262, 0.0077632262791563,
0.0181539373068718, 0.00076652557316303, 0.00409233184302446,
0.00341541300230001, 3.99254525121229e-05, 0.000187576965055149,
0.000466930324658621, 9.51568919880227e-05, 4.8860016813267e-05,
NA, 0.00196158983239875, 0.00695397443067341, 7.20351684946877e-05,
0.000157550759730307, 0.0013218211130744, 5.88088168409117e-05,
6.66613808645955e-05, 0.000111634934200908, 9.06176128855417e-05,
0.000211552540624322, NA, 0.000545166925830964, 0.000383969522519521,
8.98763657941659e-05, 0.001101400648447, 0.000407890167722191,
0.000158514368833466, 0.000487766814995315, NA, 0.000336038030038428,
0.000246298938179364, 5.27943500874004e-05, 0.000149334619314387,
0.00131509126887927, 0.000375748766387963, 6.65736995469907e-05,
0.000101855880933195, 0.000958326601909033, 0.000625100723205665,
NA, 0.000520592846361429, 0.000828228547472056, 0.000644090081901672,
0.00148329626955155, 0.00165203908371526, 0.000236853436982543,
0.000327567632167369, 0.00229629759400016, NA, 0.000600186700977042,
0.00368916150899651, 0.000486625595007798, 0.00174913110881759,
2.14852756405103e-06, 1.88877351370506e-05, 2.17169502061094e-06,
0.000886968652438946, 0.00478392888904646, NA, 0.0167025785098221,
0.00533599115238815, 0.00492026145014813, 0.0156447950402715,
0.0088887680291652, 0.00446376385202905, 0.00189896944038835,
0.000308360589278871, 0.001602731847897, NA, 0.00344494503811641,
0.00102449645908606, 0.000106518784084221, 0.00261827782410162,
0.00658086485475422, 0.000187487928691746, 0.000350981058253314,
NA, 0.000565669044174583, 0.000167158104926062, NA, 3.24612144691137e-06,
1.65397314983294e-05, 2.92443019551012e-05, 0.000102723894438066,
6.25068934519e-05, 0.00114700667444234, 0.00020384708321477,
0.000200803672792674, NA, 0.000422475568607068, 0.00043742008149273,
0.000101612546050514, 0.00154369406250457, 0.000485874486922917,
0.000531241200858085, 0.000173965248036944, 0.000821040079212838,
NA, 0.000807047252299039, 0.00301427353142851, 0.00206653182278063,
0.00116645591661203, 0.0004825912225592, 0.00149636802015173,
0.000460759215243854, 0.000209298828977479, 0.000599307844568033,
0.000493830372946341, 0.00014892762454252, NA, 7.28181078377453e-05,
3.76758311806009e-05, 0.000125680138587701, 4.90027397022612e-05,
1.88919151006188e-05, 8.52061355242569e-05, 4.09084186506651e-05,
0.000219079113625454, 0.000288385843570973, 0.000348544069690578,
4.81093175061434e-05, 9.21007017007808e-05, 0.000475776084159152,
0.000124980433307756, 6.55297072177827e-05, 9.00818802086268e-05,
5.12001601484466e-05, 4.26040356580944e-06, 7.55220608958236e-05,
3.5582285679068e-06, 3.51648567523055e-06, 0.000209192254833606,
0.000241465206244861, 3.69654103688837e-05, 2.823002331492e-05,
0.0010075550797464, 6.23276933356582e-05, 0.000261329408592834,
0.000192605100211058, 9.61743990486272e-05, 0.000147868104076224,
0.000303093749669182, 4.92940275006448e-05, 0.000317785857716085,
0.000130855366785042, 3.93468370069037e-05, 0.00314890740333094,
0.000572625173718403, 0.000440816156284809, 0.000885502377517394,
0.000517136850869312, 5.3199119107723e-05, 0.000111782316973841,
0.000126146103485941, 0.00304486739110657, 0.00136525299366371,
0.000598926363276632, 0.000268314855850743, 0.00385829870490279,
0.00129431171866651, 0.000776474172765253, 0.0012388099447595,
0.000451626342804488, 0.00025774121586828, 0.00302722558858814,
0.000789720628295024, 0.000532217196303663, 0.000280032446527994,
0.000125820189708014, 0.000115737084687623, 0.000245587635855066,
8.63860878885761e-05, 0.000929215478298609, 0.000258576460942922,
3.9032494610663e-05, 8.84170220735865e-05, 9.87724984279264e-05,
0.00024017294507176, 9.19592862675962e-05, 0.000301008650235801,
0.00104699346435116, 0.000210964615046011, 8.3305059790352e-05,
0.00141681961095272, 0.000427130871018164, 0.000592363577363505,
0.000393290141712418, 1.38720200271958e-05, 0.00249035408313262,
0.00794942394089222, 0.000601927018613472, 0.0545833018767897,
0.0181984383536397, 0.0518403941520953, 0.0639238054332242, 0.0473167646788671,
0.0692990561861212, 0.0814822415743463, 0.100755255190792, 0.0131546811074843,
0.0153130438012927, 0.000962333976405987, 0.000902518231967084,
0.000298764773549114, 0.00224948920662978, 0.000464781688997717,
0.00052303475280344, 0.0024182701684607, 0.00111776138190833)), .Names = c("Ret",
"Dum.sect", "Dum.count", "weight"))
1 ответ
Решение
Я нашел ответ в конце. По контрасту (сумме) последняя переменная просто -сумма (бета) не учитывает перехват. Это потому, что сумма (бета) = 0 при этом контрасте.
Спасибо R