TABLE 1
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Predictive performance: mean across 50 replicated datasets.

Scenario 1aScenario 1b
MOT|$\%\Delta MTU$|NPCMOT|$\%\Delta MTU$|NPC
pam-bp14.06000.019210.260014.2400−0.010613.2000
(3.2351)(0.3447)(1.9672)(2.9593)(0.3429)(2.2039)
km-bp13.42000.113011.400013.40000.075013.9600
(2.8074)(0.3038)(2.5314)(2.6108)(0.3076)(2.2584)
hc-bp12.86000.152012.020012.44000.141812.6800
(3.1429)(0.3642)(2.8961)(3.1374)(0.3403)(2.7807)
dm-int12.60000.175613.820013.28000.074012.9600
(3.4934)(0.3536)(2.9877)(3.7310)(0.3851)(3.0902)
t-ppmx10.00000.393315.160010.78000.333914.4280
(3.2451)(0.3080)(2.2800)(3.2968)(0.3362)(2.8646)
Scenario 2aScenario 2b
MOT%ΔMTUNPCMOT%ΔMTUNPC
pam-bp14.16000.014510.160014.2000−0.006813.2200
(3.2474)(0.3405)(2.2439)(2.9966)(0.3487)(2.2341)
km-bp13.36000.113612.480013.52000.068913.7800
(2.9190)(0.3082)(2.7198)(2.5414)(0.3037)(2.2883)
hc-bp12.96000.122311.540012.44000.143012.7600
(3.5165)(0.3846)(11.54)(3.1112)(0.3344)(2.7372)
dm-int12.96000.122311.540013.04000.102113.0200
(3.5165)(0.3847)(2.8082)(3.5798)(0.3627)(2.9657)
t-ppmx10.62000.357815.380010.60000.349714.4400
(3.3313)(0.3347)(2.5446)(3.1880)(0.3269)(2.8224)
Scenario 3aScenario 3b
MOT%ΔMTUNPCMOT%ΔMTUNPC
pam-bp13.98000.027511.860014.5000−0.063514.1400
(3.3654)(0.3469)(2.6955)(2.9433)(0.3310)(2.8856)
km-bp13.36000.115911.600013.70000.040513.8000
(2.8909)(0.3055)(2.6954)(2.9014)(0.3363)(2.5873)
hc-bp12.66000.162111.500012.98000.085912.3800
(3.2740)(0.3684)(2.8158)(3.3715)(0.3647)(2.3724)
dm-int12.74000.161613.900012.84000.095713.6000
(3.7461)(0.3747)(3.1445)(3.1646)(0.3548)(2.9207)
t-ppmx10.26000.361015.040010.86000.324414.8400
(3.6411)(0.3352)(2.4320)(3.1234)(0.3281)(2.6677)
Scenario 1aScenario 1b
MOT|$\%\Delta MTU$|NPCMOT|$\%\Delta MTU$|NPC
pam-bp14.06000.019210.260014.2400−0.010613.2000
(3.2351)(0.3447)(1.9672)(2.9593)(0.3429)(2.2039)
km-bp13.42000.113011.400013.40000.075013.9600
(2.8074)(0.3038)(2.5314)(2.6108)(0.3076)(2.2584)
hc-bp12.86000.152012.020012.44000.141812.6800
(3.1429)(0.3642)(2.8961)(3.1374)(0.3403)(2.7807)
dm-int12.60000.175613.820013.28000.074012.9600
(3.4934)(0.3536)(2.9877)(3.7310)(0.3851)(3.0902)
t-ppmx10.00000.393315.160010.78000.333914.4280
(3.2451)(0.3080)(2.2800)(3.2968)(0.3362)(2.8646)
Scenario 2aScenario 2b
MOT%ΔMTUNPCMOT%ΔMTUNPC
pam-bp14.16000.014510.160014.2000−0.006813.2200
(3.2474)(0.3405)(2.2439)(2.9966)(0.3487)(2.2341)
km-bp13.36000.113612.480013.52000.068913.7800
(2.9190)(0.3082)(2.7198)(2.5414)(0.3037)(2.2883)
hc-bp12.96000.122311.540012.44000.143012.7600
(3.5165)(0.3846)(11.54)(3.1112)(0.3344)(2.7372)
dm-int12.96000.122311.540013.04000.102113.0200
(3.5165)(0.3847)(2.8082)(3.5798)(0.3627)(2.9657)
t-ppmx10.62000.357815.380010.60000.349714.4400
(3.3313)(0.3347)(2.5446)(3.1880)(0.3269)(2.8224)
Scenario 3aScenario 3b
MOT%ΔMTUNPCMOT%ΔMTUNPC
pam-bp13.98000.027511.860014.5000−0.063514.1400
(3.3654)(0.3469)(2.6955)(2.9433)(0.3310)(2.8856)
km-bp13.36000.115911.600013.70000.040513.8000
(2.8909)(0.3055)(2.6954)(2.9014)(0.3363)(2.5873)
hc-bp12.66000.162111.500012.98000.085912.3800
(3.2740)(0.3684)(2.8158)(3.3715)(0.3647)(2.3724)
dm-int12.74000.161613.900012.84000.095713.6000
(3.7461)(0.3747)(3.1445)(3.1646)(0.3548)(2.9207)
t-ppmx10.26000.361015.040010.86000.324414.8400
(3.6411)(0.3352)(2.4320)(3.1234)(0.3281)(2.6677)

SDs are in parentheses. In each scenario and for each index, the best performance is in bold.

TABLE 1
Open in new tab

Predictive performance: mean across 50 replicated datasets.

Scenario 1aScenario 1b
MOT|$\%\Delta MTU$|NPCMOT|$\%\Delta MTU$|NPC
pam-bp14.06000.019210.260014.2400−0.010613.2000
(3.2351)(0.3447)(1.9672)(2.9593)(0.3429)(2.2039)
km-bp13.42000.113011.400013.40000.075013.9600
(2.8074)(0.3038)(2.5314)(2.6108)(0.3076)(2.2584)
hc-bp12.86000.152012.020012.44000.141812.6800
(3.1429)(0.3642)(2.8961)(3.1374)(0.3403)(2.7807)
dm-int12.60000.175613.820013.28000.074012.9600
(3.4934)(0.3536)(2.9877)(3.7310)(0.3851)(3.0902)
t-ppmx10.00000.393315.160010.78000.333914.4280
(3.2451)(0.3080)(2.2800)(3.2968)(0.3362)(2.8646)
Scenario 2aScenario 2b
MOT%ΔMTUNPCMOT%ΔMTUNPC
pam-bp14.16000.014510.160014.2000−0.006813.2200
(3.2474)(0.3405)(2.2439)(2.9966)(0.3487)(2.2341)
km-bp13.36000.113612.480013.52000.068913.7800
(2.9190)(0.3082)(2.7198)(2.5414)(0.3037)(2.2883)
hc-bp12.96000.122311.540012.44000.143012.7600
(3.5165)(0.3846)(11.54)(3.1112)(0.3344)(2.7372)
dm-int12.96000.122311.540013.04000.102113.0200
(3.5165)(0.3847)(2.8082)(3.5798)(0.3627)(2.9657)
t-ppmx10.62000.357815.380010.60000.349714.4400
(3.3313)(0.3347)(2.5446)(3.1880)(0.3269)(2.8224)
Scenario 3aScenario 3b
MOT%ΔMTUNPCMOT%ΔMTUNPC
pam-bp13.98000.027511.860014.5000−0.063514.1400
(3.3654)(0.3469)(2.6955)(2.9433)(0.3310)(2.8856)
km-bp13.36000.115911.600013.70000.040513.8000
(2.8909)(0.3055)(2.6954)(2.9014)(0.3363)(2.5873)
hc-bp12.66000.162111.500012.98000.085912.3800
(3.2740)(0.3684)(2.8158)(3.3715)(0.3647)(2.3724)
dm-int12.74000.161613.900012.84000.095713.6000
(3.7461)(0.3747)(3.1445)(3.1646)(0.3548)(2.9207)
t-ppmx10.26000.361015.040010.86000.324414.8400
(3.6411)(0.3352)(2.4320)(3.1234)(0.3281)(2.6677)
Scenario 1aScenario 1b
MOT|$\%\Delta MTU$|NPCMOT|$\%\Delta MTU$|NPC
pam-bp14.06000.019210.260014.2400−0.010613.2000
(3.2351)(0.3447)(1.9672)(2.9593)(0.3429)(2.2039)
km-bp13.42000.113011.400013.40000.075013.9600
(2.8074)(0.3038)(2.5314)(2.6108)(0.3076)(2.2584)
hc-bp12.86000.152012.020012.44000.141812.6800
(3.1429)(0.3642)(2.8961)(3.1374)(0.3403)(2.7807)
dm-int12.60000.175613.820013.28000.074012.9600
(3.4934)(0.3536)(2.9877)(3.7310)(0.3851)(3.0902)
t-ppmx10.00000.393315.160010.78000.333914.4280
(3.2451)(0.3080)(2.2800)(3.2968)(0.3362)(2.8646)
Scenario 2aScenario 2b
MOT%ΔMTUNPCMOT%ΔMTUNPC
pam-bp14.16000.014510.160014.2000−0.006813.2200
(3.2474)(0.3405)(2.2439)(2.9966)(0.3487)(2.2341)
km-bp13.36000.113612.480013.52000.068913.7800
(2.9190)(0.3082)(2.7198)(2.5414)(0.3037)(2.2883)
hc-bp12.96000.122311.540012.44000.143012.7600
(3.5165)(0.3846)(11.54)(3.1112)(0.3344)(2.7372)
dm-int12.96000.122311.540013.04000.102113.0200
(3.5165)(0.3847)(2.8082)(3.5798)(0.3627)(2.9657)
t-ppmx10.62000.357815.380010.60000.349714.4400
(3.3313)(0.3347)(2.5446)(3.1880)(0.3269)(2.8224)
Scenario 3aScenario 3b
MOT%ΔMTUNPCMOT%ΔMTUNPC
pam-bp13.98000.027511.860014.5000−0.063514.1400
(3.3654)(0.3469)(2.6955)(2.9433)(0.3310)(2.8856)
km-bp13.36000.115911.600013.70000.040513.8000
(2.8909)(0.3055)(2.6954)(2.9014)(0.3363)(2.5873)
hc-bp12.66000.162111.500012.98000.085912.3800
(3.2740)(0.3684)(2.8158)(3.3715)(0.3647)(2.3724)
dm-int12.74000.161613.900012.84000.095713.6000
(3.7461)(0.3747)(3.1445)(3.1646)(0.3548)(2.9207)
t-ppmx10.26000.361015.040010.86000.324414.8400
(3.6411)(0.3352)(2.4320)(3.1234)(0.3281)(2.6677)

SDs are in parentheses. In each scenario and for each index, the best performance is in bold.

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