Research Article

More on the Ridge Parameter Estimators for the Gamma Ridge Regression Model: Simulation and Applications

Table 4

EMSE, when and .

Estimators
n = 25n = 50n = 100n = 200n = 25n = 50n = 100n = 200n = 25n = 50n = 100n = 200n = 25n = 50n = 100n = 200

MLE2484.51187.2560.14290.204.56 × 106406988142161652935.82 × 1067283042308271041874.03 × 10126.50 × 1081.91 × 1071.81 × 107
k1623.13322.36167.3894.0137095968426537329184261.04 × 10616121658159270811.21 × 10108.21 × 1077.95 × 1062.90 × 106
k211.86020.84233.71955.8021.40938.221255.802236.231.53719.315760.000236.700.92471.04174.063637.127
k34.02217.416911.77915.7240.89890.86740.94781.58390.89660.86960.98961.78280.97830.95870.92850.8886
k487.61360.92048.10936.011152764195.73154.42437.7133663812.22657.72053.67.94 × 1061548063405724302
k557.75561.64269.33070.5164581.32589.63348.04258.03718.62124.22511.12931.81.86 × 106513002563026598
k61955.61102.93544.94287.252.10 × 106346837136164644262.99 × 1066135572210201027893.71 × 10103.27 × 1083.47 × 1071.15 × 107
k71538.8965.57511.20278.061.24 × 106270365121050611421.58 × 106444829188775956611.19 × 10101.68 × 1082.36 × 1079.83 × 106
k80.90610.89931.54734.33091.00030.99110.96690.91901.00140.99370.97390.93141.00481.00431.00290.9994
k91538.8965.57511.20278.061.24 × 106270365121050611421.58 × 106444829188775956611.19 × 10101.68 × 1082.36 × 1079.83 × 106
k1018.19920.56022.17922.800192.53255.39341.71459.18234.41276.37370.55468.642847.51478.21886.02729.3
k110.94561.37113.41977.89510.99120.96910.92130.89270.99420.97370.93160.89551.00421.00280.99830.9885
k120.94561.37113.41977.89510.99120.96910.92130.89270.99420.97370.93160.89551.00421.00280.99830.9885
k138.431313.02216.95419.6868.776928.32680.893193.389.074528.87382.080188.095.266613.42550.143184.91
k141.31332.80796.398411.3130.93730.87890.88801.42250.94170.88160.88251.41630.99330.97650.94080.8874
k1510.39914.58917.95720.30518.79447.867109.76226.8122.21353.319118.39229.8123.66951.313135.00366.03
k161.35532.94186.590011.4690.93780.88030.90161.51550.94330.88450.89861.51910.99450.97860.94280.8898
k17424.67343.84259.36186.67229324986.75160.04252.326739109178570.66064.14.69 × 106704942245716138955
k18278.42268.43237.49180.6530260150731868720534217921067913696173739.08 × 10722287890696131763
k191538.8965.57511.20278.061.24 × 106270365121050611421.58 × 106444829188775956611.19 × 10101.68 × 1082.36 × 1079.83 × 106
k2010.14412.77415.16216.93554.51491.700156.52254.8357.60893.393162.61260.20274.83174.20317.09677.06
k21249.14141.1987.92855.81215993524024131967371.218345638184167798947.91.71 × 1091.10 × 1071.20 × 106590990
k2219.22021.58723.02923.498218.84284.40369.25478.93276.92314.12406.64495.014312.62016.32408.23366.0
k231.00471.00451.00401.00291.00501.00501.00501.00501.00501.00501.00501.00501.00501.00501.00501.0050
k2457.75561.64269.33070.5164581.32589.63348.04258.03718.62124.22511.12931.81.86 × 107513002563026598
k251.00311.00170.99890.99341.00501.00501.00501.00491.00501.00501.00501.00491.00501.0051.00501.0050
k261538.8965.57511.20278.061.24 × 106270365121050611421.58 × 106444829188775956611.19 × 10101.68 × 1082.36 × 1079.83 × 106
k270.97670.97650.97570.97480.97750.97750.97750.97750.97750.97750.97750.97750.97750.97750.97750.9775
k282.55737.924215.98521.5910.96570.93500.97842.05960.96510.93050.99462.44420.99450.98670.96940.9459
k292.64724.98018.673512.6281.08261.78975.265416.1921.12151.87665.309817.2700.94101.01371.60123.9912
k304.40048.217812.87816.9781.70093.570811.29635.9521.88634.172612.56640.5121.41821.79373.968012.285
k314.21017.637911.94715.9281.89073.18829.831230.3941.89833.430310.53332.1781.58881.58832.88047.7587
k321.41882.49684.79687.98430.92821.04521.94935.07840.93191.04061.86935.20200.95380.92580.98431.4223
k334.80248.683313.08116.7551.65944.470313.54540.6321.56144.702214.32340.1561.00691.39583.484111.543
k340.94511.19561.80602.87960.92360.87390.91251.24200.93020.88110.91341.26100.98730.96200.91540.8843
k352.11473.87246.73949.86070.94421.22992.69957.10670.93601.19462.59296.73810.96500.93090.95761.3561
k367.462012.62117.45620.9811.91303.29258.694229.0842.38744.504411.07635.8263.31751.93662.94606.6976
k3710.47614.22018.82120.26114.85924.04051.993107.958.1316111.8050.927105.628.207118.88948.99778.194
k389.453013.21116.71819.32212.38520.97843.90498.88912.66821.57144.81699.07958.22213.41421.21447.468
k39249.14141.1987.92855.81215993524024131967371.218345638184167798947.91.71 × 1091.10 × 1071.20 × 106590990
k400.96221.46303.86508.79110.99060.96700.91860.90410.99350.97150.92590.89201.00411.00240.99740.9863