Two scales are available. With structural = TRUE (the default)
these are the fitted values of y = alpha_i + x'beta + z'delta +
e on the original rows; with structural = FALSE they are the
fitted values of the FOD-transformed model on the transformed rows.
Usage
# S3 method for class 'copregpanel'
fitted(object, structural = TRUE, ...)Examples
# \donttest{
set.seed(1)
N <- 30L; Time <- 6L
d <- data.frame(id = rep(seq_len(N), each = Time),
year = rep(seq_len(Time), times = N))
alpha <- rep(rnorm(N), each = Time)
e <- rnorm(N * Time)
d$x <- exp(rnorm(N * Time) + 0.5 * e) # endogenous: correlated with e
d$z <- rnorm(N * Time) # exogenous
d$y <- alpha + 0.5 * d$x + d$z + e
fit <- CopRegPANEL(y ~ x | z, data = d, index = c("id", "year"),
nboots = 15, verbose = FALSE)
fitted(fit)
#> 1 2 3 4 5 6
#> 1.44546508 0.66834012 0.81700289 -0.19393154 -0.06388554 0.29170856
#> 7 8 9 10 11 12
#> 2.21143700 0.59410300 1.31059876 1.90316677 1.51227529 2.63056302
#> 13 14 15 16 17 18
#> -0.87410321 -0.58578073 -0.95035574 1.00779036 -0.59976921 -0.80225815
#> 19 20 21 22 23 24
#> 3.50027530 1.89261933 1.44031839 2.22655252 2.95043812 1.33934141
#> 25 26 27 28 29 30
#> 1.22698873 2.44493012 2.44493085 0.63883846 1.33206461 2.84683909
#> 31 32 33 34 35 36
#> 4.22858964 0.30800598 0.44571812 -1.79427040 1.25513745 1.26183510
#> 37 38 39 40 41 42
#> -0.64900150 0.81571481 0.61504785 4.05177774 -0.44386507 1.76031252
#> 43 44 45 46 47 48
#> -0.36374619 0.69066427 1.55117364 2.02506470 1.35882592 1.30087191
#> 49 50 51 52 53 54
#> 0.46968085 1.20586812 0.88000368 2.33962301 0.99137415 1.69268676
#> 55 56 57 58 59 60
#> 3.83415034 -2.03811888 -0.69212694 -0.20820759 0.70273999 -1.93294449
#> 61 62 63 64 65 66
#> 3.57383759 3.10468263 2.03648039 10.45910667 2.24055340 4.38513030
#> 67 68 69 70 71 72
#> 0.22826332 -1.51152688 -1.15823497 1.16921727 -0.18726897 2.09044831
#> 73 74 75 76 77 78
#> 2.07604694 0.58334150 -0.03808712 0.45224286 -0.55262682 2.28755491
#> 79 80 81 82 83 84
#> 0.42048991 2.16924983 -2.40113479 -2.84654926 -0.72843123 -1.36798714
#> 85 86 87 88 89 90
#> 4.85874195 0.24559622 2.26001004 2.33992051 2.75126942 1.33860849
#> 91 92 93 94 95 96
#> 0.80423033 -0.51752863 2.81734769 0.19346548 4.82485567 5.63148702
#> 97 98 99 100 101 102
#> 0.06889917 -0.43478709 -2.01418626 0.77316922 0.08942130 2.27806512
#> 103 104 105 106 107 108
#> 0.02309268 0.68645784 4.60058022 0.06072587 1.00867305 -0.25631265
#> 109 110 111 112 113 114
#> 0.68075843 0.19079838 1.00648484 3.80408655 -0.39259449 0.32702344
#> 115 116 117 118 119 120
#> 1.55827824 2.20213119 -0.16806509 0.51367136 1.38145457 -0.45907742
#> 121 122 123 124 125 126
#> -1.62220450 -0.44880744 -0.29565493 1.55140666 0.11767292 1.13399108
#> 127 128 129 130 131 132
#> 2.62105901 1.70347148 0.82145285 2.83720508 1.53542667 1.42026956
#> 133 134 135 136 137 138
#> 0.59479256 1.14925179 0.38937395 -0.84306739 1.30809278 1.70593277
#> 139 140 141 142 143 144
#> 0.23645547 2.22302460 4.06117010 0.69644928 -0.44648191 -1.44462433
#> 145 146 147 148 149 150
#> 4.97700450 1.59750511 1.98096435 3.83592349 2.16195170 1.90179599
#> 151 152 153 154 155 156
#> -0.56496486 3.04032995 0.57736889 -0.02277345 1.57766638 0.55904076
#> 157 158 159 160 161 162
#> 1.07687753 0.86943548 -2.07420417 0.23660112 0.55426338 0.34484328
#> 163 164 165 166 167 168
#> -2.66878464 -1.45902655 -0.21300435 -2.18135847 -2.84926604 -0.74343717
#> 169 170 171 172 173 174
#> 0.15988673 1.94730481 0.24024089 3.47798535 1.21768370 0.05751085
#> 175 176 177 178 179 180
#> 0.67769444 3.37226437 0.61468208 1.49845779 0.24866535 1.89298101
fitted(fit, structural = FALSE)
#> 1 2 3 4 5 7
#> 1.042150047 0.407515811 0.697761626 -0.251352797 -0.251443003 0.567162723
#> 8 9 10 11 13 14
#> -1.113604754 -0.610319510 -0.137377493 -0.790748834 -0.445507047 -0.223278139
#> 15 16 17 19 20 21
#> -0.709225796 1.395232659 0.143181301 1.397077157 -0.086350935 -0.633750721
#> 22 23 25 26 27 28
#> 0.066677359 1.139217410 -0.652275397 0.562828927 0.726609861 -1.184420874
#> 29 31 32 33 34 35
#> -1.071107302 3.590599229 0.014222211 0.177377078 -2.492565390 -0.004735951
#> 37 38 39 40 41 43
#> -1.833774269 -0.608303018 -1.017026063 2.770825248 -1.558588917 -1.596671756
#> 44 45 46 47 49 50
#> -0.776648814 -0.009018673 0.567641315 0.040979674 -0.869263358 -0.241543441
#> 51 52 53 55 56 57
#> -0.688107089 0.814530910 -0.495902906 4.261173709 -1.346545934 -0.184165708
#> 58 59 61 62 63 64
#> 0.332228098 1.863710368 -0.795432907 -1.498733560 -3.168310406 5.834900791
#> 65 67 68 69 70 71
#> -1.516444874 0.134864241 -1.779970298 -1.889985417 0.177692193 -1.610589333
#> 73 74 75 76 77 79
#> 1.396292568 0.041206743 -0.664366279 -0.339026682 -2.008311763 1.328647512
#> 80 81 82 83 85 86
#> 3.582427260 -0.652531883 -1.468338524 0.452234327 2.804030048 -1.723432307
#> 87 88 89 91 92 93
#> 0.101103182 0.240851437 0.998902123 -1.630109157 -3.474239277 -0.634440139
#> 94 95 97 98 99 100
#> -4.110820123 -0.570374495 -0.063387285 -0.640771605 -2.650965659 -0.335232257
#> 101 103 104 105 106 107
#> -1.547604884 -1.092644600 -0.596546069 3.749501549 -0.257567383 0.894479966
#> 109 110 111 112 113 115
#> -0.279704851 -0.890359069 -0.207575023 3.132792933 -0.508846722 0.788953554
#> 116 117 118 119 121 122
#> 1.686116303 -0.560100134 0.042852017 1.301452651 -1.856712062 -0.962100776
#> 123 124 125 127 128 129
#> -1.065221481 0.755728543 -0.718645461 0.874068326 0.044616661 -0.960867536
#> 130 131 133 134 135 136
#> 1.109910313 0.081428373 -0.134305424 0.455414385 -0.289493912 -1.918832418
#> 137 139 140 141 142 143
#> -0.281315357 -0.713364882 1.347361822 3.861944239 1.340689342 0.705793271
#> 145 146 147 148 149 151
#> 2.447750539 -0.780525262 -0.564873189 1.473000371 0.183957867 -1.562188135
#> 152 153 154 155 157 158
#> 2.117560223 -0.110223963 -0.890901479 0.720277086 0.995658926 0.987500909
#> 159 160 161 163 164 165
#> -2.124164106 -0.173874750 0.148082372 -1.076791629 0.033755644 1.482360859
#> 166 167 169 170 171 172
#> -0.314356784 -1.489045872 -1.121241377 0.625159536 -1.164070130 2.319167155
#> 173 175 176 177 178 179
#> 0.820366088 -0.773855003 2.064845822 -0.518477259 0.349162199 -1.162706751
# }