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master's thesis
Primjena Jackknife metode na linearni regresijski model za procjenu rasta poduzeća
2023. urn:nbn:hr:126:783586
Lozina, Nikolina
Josip Juraj Strossmayer University of Osijek
School of Applied Mathematics and Informatics

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Lozina, N. (2023). Primjena Jackknife metode na linearni regresijski model za procjenu rasta poduzeća (Master's thesis). Osijek: Josip Juraj Strossmayer University of Osijek, School of Applied Mathematics and Informatics. Retrieved from https://urn.nsk.hr/urn:nbn:hr:126:783586

Lozina, Nikolina. "Primjena Jackknife metode na linearni regresijski model za procjenu rasta poduzeća." Master's thesis, Josip Juraj Strossmayer University of Osijek, School of Applied Mathematics and Informatics, 2023. https://urn.nsk.hr/urn:nbn:hr:126:783586

Lozina, Nikolina. "Primjena Jackknife metode na linearni regresijski model za procjenu rasta poduzeća." Master's thesis, Josip Juraj Strossmayer University of Osijek, School of Applied Mathematics and Informatics, 2023. https://urn.nsk.hr/urn:nbn:hr:126:783586

Lozina, N. (2023). 'Primjena Jackknife metode na linearni regresijski model za procjenu rasta poduzeća', Master's thesis, Josip Juraj Strossmayer University of Osijek, School of Applied Mathematics and Informatics, accessed 28 December 2024, https://urn.nsk.hr/urn:nbn:hr:126:783586

Lozina N. Primjena Jackknife metode na linearni regresijski model za procjenu rasta poduzeća [Master's thesis]. Osijek: Josip Juraj Strossmayer University of Osijek, School of Applied Mathematics and Informatics; 2023 [cited 2024 December 28] Available at: https://urn.nsk.hr/urn:nbn:hr:126:783586

N. Lozina, "Primjena Jackknife metode na linearni regresijski model za procjenu rasta poduzeća", Master's thesis, Josip Juraj Strossmayer University of Osijek, School of Applied Mathematics and Informatics, Osijek, 2023. Available at: https://urn.nsk.hr/urn:nbn:hr:126:783586

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Metadata
TitlePrimjena Jackknife metode na linearni regresijski model za procjenu rasta poduzeća
Title (english)Jackknife Method Application To A Linear Regression Model Of Company Growth
AuthorNikolina Lozina
MentorNataša Šarlija (mentor)
MentorMirta Benšić (komentor)
Committee memberIvan Papić (predsjednik povjerenstva)
Committee memberMirta Benšić (član povjerenstva)
Committee memberNataša Šarlija (član povjerenstva)
GranterJosip Juraj Strossmayer University of Osijek
School of Applied Mathematics and Informatics
Osijek
Defense date and country2023-10-16, Croatia
Scientific / art field,
discipline and subdiscipline		NATURAL SCIENCES
Mathematics
Abstract
U radu je predstavljena jackknife metoda ponovljenog uzorkovanja i njena primjena na linearni regresijski model. U prvom dijelu rada kratko su predstavljeni osnovni pojmovi i pretpostavke linearne regresije. Zatim je predstavljena jacknnife metoda i njena primjena u statistici. Drugi dio rada obuhvaća izgradnju linearnog regresijskog modela za procjenu rasta malih i srednjih poduzeća na temelju podataka prikupljenih od 156 hrvatskih poduzeća u razdoblju 2012. − 2015. U dobivenom regresijskom modelu nije prisutan problem multikolinearnosti, kao ni heteroskedastičnosti, te je logičan i u skladu s prethodnim istraživanjima. Jackknife metoda za izračun standardne greške procjenitelja i pouzdanih intervala primjenjena je na regresijski model i usporedeni su dobiveni rezultati.
Abstract (english)
In this paper we introduced jackknife method and its application to linear regression model. The basic terms and assumptions of linear regression are briefly presented in the first part of the paper as well as the jackknife method and its application in statistics. The second part of the paper includes the construction of linear regression model for estimating the growth of small and medium-sized enterprises based on data collected from 156 Croatian enterprises in the period 2012. − 2015. The obtained regression model has no problem of multicollinearity, nor heteroscedasticity, and it is logical and in accordance with previous research. The jackknife method for calculating the standard error of the estimator and confidence intervals was applied to the regression model and the given results were compared.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:126:783586
Study programmeTitle: Mathematics; specializations in: Financial and Statistical Mathematics, Mathematics and Computer Science, Industrial and Applied Mathematics
Course: Financial and Statistical Mathematics
Study programme type: university
Study level: graduate
Academic / professional title: magistar/magistra matematike (magistar/magistra matematike)
Type of resourceText
File originBorn digital
Access conditionsOpen access
Terms of useLicence In copyright icon
Created on2023-11-10 10:22:15