Penentuan Distribusi Sample Terbatas Uji-J Davidson dan Mackinnon dengan Metode Bootstrap pada Model Regresi Tak Tersarang

Tinungki, Georgina M.

doi:10.20956/jmsk.v15i2.5708

Jurnal

Penentuan Distribusi Sample Terbatas Uji-J Davidson dan Mackinnon dengan Metode Bootstrap pada Model Regresi Tak Tersarang

Tinungki, Georgina M.

Jurnal Matematika, Statistika dan Komputasi · Vol. 15 No. 2 (2018) · pp. 1–9

DOI: 10.20956/jmsk.v15i2.5708
ISSN: 2614-8811, 1858-1382
Published: 2018-12-20
Publisher: Department of Mathematics, Hasanuddin University
Language: en

Abstract

Georgina Maria Tinungki* AbstractThere are some tests proposed for un-nested hypothesis between J-Davidson Test and MacKinnon Test. J’s Test is often bad result, but it always works very well when used bootstrap. Bootstrapping for J’s Test is expected to be able to show that by using bounded sample is better, because there is no fault in counting process. Moreover, bootstrapping J-Test will omit the possibility of inconsistence of the results test previously. Simulation result of Monte Carlo will compare the proposed bounded sample test with Cox and J’s Test previously. Keywords: un-nested hypothesis, J-Davidson Test, MacKinnon Test AbstrakTerdapat beberapa pengujian yang diusulkan untuk hipotesis tak tersarang antara lain Uji-J Davidson dan MacKinnon. Uji-J sering bekerja buruk, tetapi biasanya bekerja sangat baik ketika dibootstrapkan.. Bootstrapping Uji-J diharapkan mampuh menunjukkan sampel terbatas lebih baik karena tidak mempunyai kesalahan didalam proses perhitungan. Lebih dari itu, bootstrapping J-Tests akan mengeluarkan kemungkinan dari ketidak konsistenan hasil uji yang sebelumnya. Hasil Simulasi Monte Carlo membandingkan uji sampel terbatas yang diusulkan dengan test yang sebelumnya seperti Uji Cox dan J-Test. Kata Kunci: Hipotesis tak tersarang,, Uji-J Davidson, Uji MacKinnon

Keywords

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7 authors · 9 co-authorship links

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Jenderal Soedirman University
Affiliation unknown

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Co-author	Organisation	Joint articles
Nurtiti Sunusi	Affiliation unknown	2
Amran Amran	Jenderal Soedirman University	1
Hanifah Lainun	Affiliation unknown	1
Aidawayati Rangkuti	Affiliation unknown	1
Aprizal Resky	Affiliation unknown	1
Nur Aminah Ahmad	Affiliation unknown	1

Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

Metadata source: OAI-PMH (metadata jurnal) https://journal.unhas.ac.id/index.php/jmsk/oai, first harvested 5 Nov 2026, last seen 5 Nov 2026.

Original metadata (oai_dc)

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	<dc:title xml:lang="en">Penentuan Distribusi Sample Terbatas Uji-J Davidson dan Mackinnon dengan  Metode Bootstrap pada Model  Regresi Tak Tersarang</dc:title>
	<dc:creator xml:lang="en">Tinungki, Georgina M.</dc:creator>
	<dc:subject xml:lang="en">un-nested hypothesis</dc:subject>
	<dc:subject xml:lang="en">J-Davidson Test</dc:subject>
	<dc:subject xml:lang="en">MacKinnon Test</dc:subject>
	<dc:description xml:lang="en">Georgina Maria Tinungki* AbstractThere are some tests proposed for un-nested hypothesis between J-Davidson Test  and MacKinnon Test. J’s Test is often bad result, but it always works very well when used bootstrap. Bootstrapping   for J’s Test is expected to be able to show that by using bounded sample is better, because there is no fault in counting process. Moreover, bootstrapping J-Test will omit the possibility of inconsistence of the results test previously. Simulation result of Monte Carlo will compare the proposed bounded sample test with Cox and J’s Test previously. Keywords: un-nested hypothesis, J-Davidson Test, MacKinnon Test                                                                 AbstrakTerdapat beberapa pengujian yang diusulkan untuk hipotesis tak tersarang antara lain Uji-J Davidson dan MacKinnon. Uji-J sering bekerja buruk, tetapi biasanya bekerja sangat baik ketika dibootstrapkan.. Bootstrapping Uji-J diharapkan mampuh menunjukkan sampel terbatas lebih baik karena tidak mempunyai kesalahan didalam proses perhitungan. Lebih dari itu, bootstrapping J-Tests akan mengeluarkan kemungkinan dari ketidak konsistenan hasil uji yang sebelumnya. Hasil Simulasi Monte Carlo membandingkan uji sampel terbatas yang diusulkan dengan test yang sebelumnya seperti Uji Cox  dan J-Test. Kata Kunci:    Hipotesis tak tersarang,,  Uji-J Davidson,  Uji MacKinnon</dc:description>
	<dc:publisher xml:lang="en">Department of Mathematics, Hasanuddin University</dc:publisher>
	<dc:date>2018-12-20</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
	<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
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	<dc:identifier>https://journal.unhas.ac.id/index.php/jmsk/article/view/5708</dc:identifier>
	<dc:identifier>10.20956/jmsk.v15i2.5708</dc:identifier>
	<dc:source xml:lang="en">Jurnal Matematika, Statistika dan Komputasi; Vol. 15 No. 2 (2019): JMSK Vol. 15, No. 2, January 2019; 1-9</dc:source>
	<dc:source>2614-8811</dc:source>
	<dc:source>1858-1382</dc:source>
	<dc:language>en</dc:language>
	<dc:relation>https://journal.unhas.ac.id/index.php/jmsk/article/view/5708/3133</dc:relation>
	<dc:relation>10.20956/j.v15i2.5708.g3133</dc:relation>
	<dc:rights xml:lang="en">Copyright (c) 2018 Jurnal Matematika Statistika dan Komputasi</dc:rights>
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