Academic literature on the topic 'Factor Analysi'
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Journal articles on the topic "Factor Analysi"
Erawati, Teguh, and Sisilia Stefani Wuarlela. "Ukuran Perusahaan, Profitabilitas, Likuiditas, Pertumbuhan Laba Dan Kualitas Laba Pada Perusahaan Pertambangan Di Indonesia." Jurnal Literasi Akuntansi 2, no. 2 (August 5, 2022): 157–66. http://dx.doi.org/10.55587/jla.v2i2.62.
Full textErawati, Teguh, and Sisilia Stefani Wuarlela. "Ukuran Perusahaan, Profitabilitas, Likuiditas, Pertumbuhan Laba Dan Kualitas Laba Pada Perusahaan Pertambangan Di Indonesia." Jurnal Literasi Akuntansi 2, no. 2 (August 5, 2022): 157–66. http://dx.doi.org/10.55587/jla.v2i2.62.
Full textKratochvíl, Petr. "The determination of factors in linear models of factor analysis." Applications of Mathematics 35, no. 5 (1990): 350–55. http://dx.doi.org/10.21136/am.1990.104416.
Full textBudi S, Surawan Setya. "PENGARUH INPUT PROSES RELATIONSHIP MARKETING TERHADAP OUTPUT PROSES RELATIONSHIP MARKETING." Kajian Bisnis STIE Widya Wiwaha 27, no. 2 (July 24, 2019): 190–206. http://dx.doi.org/10.32477/jkb.v27i2.349.
Full textS, Surawan Setya Budi. "PENGARUH INPUT PROSES RELATIONSHIP MARKETING TERHADAP OUTPUT PROSES RELATIONSHIP MARKETING STUDI KASUS GRAND INNA MALIOBORO HOTEL & CONVENTION." Kajian Bisnis Sekolah Tinggi Ilmu Ekonomi Widya Wiwaha 27, no. 2 (August 31, 2019): 190–206. http://dx.doi.org/10.32477/jkb.v27i2.62.
Full textDr.G.Kalaivanan, Dr G. Kalaivanan, and B. Ussaima B.Ussaima. "Factors Attracting Children to View TV Commercials - A Study Using Factor Analysis." Indian Journal of Applied Research 4, no. 6 (October 1, 2011): 71–73. http://dx.doi.org/10.15373/2249555x/june2014/21.
Full textDevica, Sadana. "PERSEPSI KONSUMEN TERHADAP FLASH SALE BELANJA ONLINE DAN PENGARUHNYA PADA KEPUTUSAN PEMBELIAN." Jurnal Bisnis Terapan 4, no. 1 (June 26, 2020): 47–56. http://dx.doi.org/10.24123/jbt.v4i1.2276.
Full textPattnaik, Sudhanshu. "An Empirical Investigation into the Factors Influencing While Purchasing Car in India-A Confirmatory Factor Analysis." Journal of Advanced Research in Dynamical and Control Systems 11, no. 10-SPECIAL ISSUE (October 25, 2019): 404–10. http://dx.doi.org/10.5373/jardcs/v11sp10/20192821.
Full textMajumdar, Dr Kakali. "Factor Analysis and Business Research." Indian Journal of Applied Research 1, no. 6 (October 1, 2011): 151–54. http://dx.doi.org/10.15373/2249555x/mar2012/52.
Full textGurčík, Ľ., and V. Jančíková. "Factor analysis of owners equity effectiveness." Agricultural Economics (Zemědělská ekonomika) 48, No. 5 (February 29, 2012): 229–32. http://dx.doi.org/10.17221/5308-agricecon.
Full textDissertations / Theses on the topic "Factor Analysi"
OPERTI, VALERIO. "Travellers¿ Preferences and Attitudes to understand Travel Behaviour and define Market Segmentation." Doctoral thesis, Politecnico di Torino, 2019. http://hdl.handle.net/11583/2739920.
Full textSCOZZA, EMILIANO. "Absolute risk analysis applied to contaminated sites." Doctoral thesis, Università degli Studi di Roma "Tor Vergata", 2009. http://hdl.handle.net/2108/1106.
Full textThe instrument 'Risk Analysis' for the assessment of contaminated sites has been used for several years and has received a strong boost in the U.S. in the framework of the Superfund Program and in Italy has gained wider relevance after the introduction of new environmental legislation. Risk analysis is currently the most advanced procedure for the evaluation of the degree of contamination of an area and to define the priorities and modalities of intervention in the site itself. The risk analysis procedure can be conducted in forward mode or backward mode. The forward mode allows estimating the health risk for the exposed receptor, whether located near the site (on-site) or at some distance (off-site), given the concentration at the source of contamination. Having instead set the level of risk to health considered acceptable to the exposed receptor, the backward mode allows the calculation of the highest concentration at the source compatible with the condition of acceptability of the risk, i.e. the so-called site-specific target level. The Italian Agency for Environmental Protection (now ISPRA, formerly APAT) has recently issued a guideline document that provides a standard procedure for application of risk analysis to contaminated sites. This guideline document is based on a Tier 2 risk analysis approach, which is based on a series of simplifying assumptions: • Contaminant transport is described through the analytical equations which are not validated with experimental data or with numerical model results. • Attenuation of contaminant through biodegradation phenomena is not accounted for; • Exposure to contaminants through the food chain is neglected. Besides, when this thesis was started, the document included only the procedure for applying the risk analysis in forward mode. The work performed within this PhD thesis, supported by APAT, was to upgrade the procedure for application of risk analysis to contaminated sites, including also the unresolved issues listed above. In chapter 1, after a short background on the fundamentals of risk analysis, a procedure to obtain the threshold risk concentration, as requested by the new Italian legislation (D.M. 152/06) was developed. In chapter 2 the assumption and the procedure suggested by several technical documents and software on the exposure through the food chain were analyzed and a standard procedure was suggested for implementation in the risk analysis framework. In chapter 3 the results of the analytical equation selected for tier II risk analysis were compared with those provided by numerical transport models. The validation of the equations for Tier 2 risk analysis was performed on two key transport factors: • The Leaching Factor, LF, which describes the contaminant transport through the vadose zone; • The Dilution Attenuation Factor, DAF, which describes the contaminant transport through the acquifer. In chapter 4 the influence of the vadose zone biodegradation related to the indoor vapour intrusion was studied in order to understand how this phenomena can influence the chemical volatilization to indoor environment. Besides, in the framework of the PhD activities, a risk analysis software, based on the APAT guidelines, was developed and linked to a database of the chemical and toxicological properties of the contaminants, properly developed.
GIOVANNELLI, ALESSANDRO. "Nonlinear forecasting using a large number of predictors." Doctoral thesis, Università degli Studi di Roma "Tor Vergata", 2010. http://hdl.handle.net/2108/1333.
Full textThis dissertation aims to introduce a nonlinear model to forecast macroeconomic time series using a large number of predictors, namely the Feedforward Neural Network - Dynamic Factor Model (FNN-DF). The technique used to summarize the predictors in a small number of factors is Generalized Dynamic Factor Model, while the method used to capture nonlinearity is artificial neural networks, specifically Feedforward Neural Network. Commonly in GDFM literature, forecasts are made using linear models. However linear techniques are often misspecified and the resulting forecasts provide only a poor approximation to the best possible forecast. In an effort to address this issue, the technique we propose is FNN-DF. To determine the practical usefulness of the model, we conducted several pseudo forecasting exercises on 8 series of the United States economy. The series we were interested in forecasting were grouped in real and nominal categories. This method was used to construct the forecasts at 1-, 3-, 6-, 9 and 12-month horizons for monthly U.S. economic variables using 131 predictors. The empirical study shows that FNN-DF has good ability to predict the variables under study in the period before the start of the "Great Moderation", namely 1984. After 1984, FNN-DF has the same accuracy in forecasting with respect to the benchmark.
COMOTTI, ANNA. "Assessing psychometric scales through IRT-based modelling with application to COVID-19 data." Doctoral thesis, Università degli Studi di Milano-Bicocca, 2022. http://hdl.handle.net/10281/365350.
Full textA latent trait is an unobservable psychological attribute of an individual. A common way to measure it relies on the use of questionnaires, which collect person’s responses to test items and calculate a score representing the underlying latent trait. We analysed data collected among health care workers (HCWs) who faced COVID-19 pandemic and whose psychological wellbeing was evaluated through psychometric scales (GHQ-12, IES-r, GAD-7). Classical test theory (CTT) and item response theory (IRT) represent two different measurement frameworks. Starting from a series of clinical questions arising from a specific medical environment, objectives of this work were to explore the clinical implication of the tests’ outcome, performed through risk factor analysis for psychological impairment on a sample of 990 HCWs, and to evaluate the structure of the scales intended as measurement tools. We provided demonstration of the utility of IRT as compared with CTT-based method through the analysis of General Health Questionnaire – 12 (GHQ-12 questionnaire), a valid and reliable tool widely used to measure mental health. IRT-based techniques enable us to delve in several areas of interest of GHQ-12 questionnaire. Through the multidimensional version of IRT models we assess its dimensionality, finding that HCWs' psychological wellbeing was affected by general discomfort and stress together with a strong feeling of uselessness and inability to make decisions. Differential item functioning (DIF) detection performed with IRT investigated possible differences in responses between subjected directly or indirectly involved with COVID-19 patients and between workers enrolled before or after vaccination campaign, showing how their psychological status was affected by such circumstances. The discrete version of IRT (based on latent class analysis) allowed to determine how some response pattern may predict individual’s outcome of psychological wellbeing evaluation which consisted in three steps. Lastly, we explored the issue of atypical response pattern detection applying Forward Search algorithm to Rasch model.
GRATTON, PAOLO. "Phylogeography and conservation genetics of parnassius mnemosyne l. : 1758 (lepidoptera, papilionidae)." Doctoral thesis, Università degli Studi di Roma "Tor Vergata", 2005. http://hdl.handle.net/2108/202665.
Full textPresent work is addressed at providing basic information about relationships between patterns of geographic distribution and genetic variation in populations of the montane butterfly Parnassius mnemosyne. A total of 172 individuals from 58 localities representing most of the species range have been sequenced at part of two mitochondrial genes (COI and ND5) and one nuclear gene (EF-1α). A sample of 397 individuals from 16 italian localities (Central-Eastern Alps, Central Apennine and Sicily) has been characterized at 5 newly developed microsatellite loci. Phylogeographic analysis of mitochondrial and nuclear sequences showed that P. mnemosyne populations bear genetic traces of a geographic history about one million years long. Highly divergent mitochondrial lineages mark at least two evolutionarily significant units in Europe, which may indeed represent different species. Nested Clade Analysis was employed in a reconstruction of the main stages of the history of the species during the Pleistocene, including possible evidences of survival in Northern refugia during last glacial episodes. Novel microsatellite markers have been tested on some critical areas and provided evidences of genetic structuring at the scale of a few kilometers. Marked reduction of genetic variability was evidenced in “marginal” populations from Monti Aurunci (Lazio) and Sicily. Results are meant to offer a genetically based framework for planning future conservation effort.
RONCALLO, LUCA. "Evolutionary spectral model for thunderstorm outflows and application to the analysis of the dynamic response of structures." Doctoral thesis, Università degli studi di Genova, 2022. http://hdl.handle.net/11567/1080956.
Full textWang, Jing. "Analogy Between Two Approaches to Separately Identify Specific Factors in Factor Analysis." Bowling Green State University / OhioLINK, 2007. http://rave.ohiolink.edu/etdc/view?acc_num=bgsu1182784851.
Full textCool, Deborah E. "Characterization of the human factor XII (Hageman factor) CDNA and the gene." Thesis, University of British Columbia, 1987. http://hdl.handle.net/2429/26980.
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Biochemistry and Molecular Biology, Department of
Graduate
POMA, GIULIA. "Evaluation of bioaccumulation processes of brominated flame retardants in biotic matrices." Doctoral thesis, Università degli Studi di Milano-Bicocca, 2014. http://hdl.handle.net/10281/50902.
Full textKarimi, Mahdad. "Functional analysis of the -308G/A polymorphism in the tumour necrosis factor promoter." University of Western Australia. School of Biomedical, Biomolecular and Chemical Sciences, 2007. http://theses.library.uwa.edu.au/adt-WU2007.0140.
Full textBooks on the topic "Factor Analysi"
Foundations of factor analysis. 2nd ed. Boca Raton: CRC Press, 2010.
Find full textBánkövi, Gy. Dynamic factor analysis. Budapest: Karl Marx University of Economics, Dept. of Mathematics and Computer Sciences, 1986.
Find full textTheodore, Wegener Duane, ed. Exploratory factor analysis. Oxford: Oxford University Press, 2012.
Find full textConfirmatory factor analysis. New York, N.Y: Oxford University Press, 2009.
Find full textFactor analysis and related methods. Hillsdale, N.J: Lawrence Erlbaum Associates, 1985.
Find full textBartholomew, David J. Latent variable models and factor analysis. 2nd ed. London: Arnold, 1999.
Find full textBartholomew, David J. Latent variable models and factor analysis. London: C. Griffin, 1987.
Find full textMalinowski, Edmund R. Factor analysis in chemistry. 2nd ed. New York: Wiley, 1991.
Find full textMalinowski, Edmund R. Factor analysis in chemistry. Malabar, Fla: R.E. Krieger Pub. Co., 1989.
Find full textFactor analysis in chemistry. 3rd ed. New York: Wiley, 2002.
Find full textBook chapters on the topic "Factor Analysi"
Backhaus, Klaus, Bernd Erichson, Sonja Gensler, Rolf Weiber, and Thomas Weiber. "Factor Analysis." In Multivariate Analysis, 381–450. Wiesbaden: Springer Fachmedien Wiesbaden, 2021. http://dx.doi.org/10.1007/978-3-658-32589-3_7.
Full textLovik, Anikó, Vahid Nassiri, Geert Verbeke, and Geert Molenberghs. "Combining Factors from Different Factor Analyses Based on Factor Congruence." In Springer Proceedings in Mathematics & Statistics, 211–19. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-77249-3_18.
Full textSarstedt, Marko, and Erik Mooi. "Factor Analysis." In Springer Texts in Business and Economics, 235–72. Berlin, Heidelberg: Springer Berlin Heidelberg, 2014. http://dx.doi.org/10.1007/978-3-642-53965-7_8.
Full textCleff, Thomas. "Factor Analysis." In Applied Statistics and Multivariate Data Analysis for Business and Economics, 433–46. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-17767-6_13.
Full textHärdle, Wolfgang Karl, and Zdeněk Hlávka. "Factor Analysis." In Multivariate Statistics, 205–24. Berlin, Heidelberg: Springer Berlin Heidelberg, 2015. http://dx.doi.org/10.1007/978-3-642-36005-3_12.
Full textActon, Ciaran, Robert Miller, John Maltby, and Deirdre Fullerton. "Factor Analysis." In SPSS for Social Scientists, 241–55. London: Macmillan Education UK, 2009. http://dx.doi.org/10.1007/978-1-137-01390-3_11.
Full textMiller, Robert L., Ciaran Acton, Deirdre A. Fullerton, John Maltby, and Jo Campling. "Factor Analysis." In SPSS for Social Scientists, 174–85. London: Macmillan Education UK, 2002. http://dx.doi.org/10.1007/978-0-230-62968-4_10.
Full textFranzen, Michael D. "Factor Analysis." In Encyclopedia of Clinical Neuropsychology, 1013. New York, NY: Springer New York, 2011. http://dx.doi.org/10.1007/978-0-387-79948-3_1195.
Full textHärdle, Wolfgang, and Léopold Simar. "Factor Analysis." In Applied Multivariate Statistical Analysis, 275–99. Berlin, Heidelberg: Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/978-3-662-05802-2_10.
Full textFranzen, Michael. "Factor Analysis." In Encyclopedia of Clinical Neuropsychology, 1. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-56782-2_1195-2.
Full textConference papers on the topic "Factor Analysi"
Melgaard, D. K., A. J. Scholand, and K. W. Larson. "Scene kinetics mitigation using factor analysis with derivative factors." In SPIE Optical Engineering + Applications, edited by Andrew G. Tescher. SPIE, 2010. http://dx.doi.org/10.1117/12.863950.
Full textMarjaie, Seyed Ali, and Vasundhara Kulkarni. "Recognition of Hidden Factors in Requirements Prioritization Using Factor Analysis." In 2010 International Conference on Computational Intelligence and Software Engineering (CiSE). IEEE, 2010. http://dx.doi.org/10.1109/cise.2010.5676794.
Full textYuan, Xiang. "Based on factor analysis of influencing factors of port throughput." In 2011 International Conference on Photonics, 3D-imaging, and Visualization. SPIE, 2011. http://dx.doi.org/10.1117/12.906094.
Full textXiong, Zhangyuan, Hongzhi Yu, Lulu Liu, and Fucheng Wan. "Analysis of Product Competitive Factors in Agricultural B2C Platform Based on Factor Analysis." In 2016 5th International Conference on Measurement, Instrumentation and Automation (ICMIA 2016). Paris, France: Atlantis Press, 2016. http://dx.doi.org/10.2991/icmia-16.2016.89.
Full textZhou, Xiaofen, Rongyan Zhu, Yong Wang, and Gongzhuo Xu. "Analysis of Factors Influencing Consumer Behavior of Mobile Commerce based on Factor Analysis." In Proceedings of The First International Symposium on Management and Social Sciences (ISMSS 2019). Paris, France: Atlantis Press, 2019. http://dx.doi.org/10.2991/ismss-19.2019.13.
Full textWu, Xilan. "Main Factor Analysis of Influencing Factors of College Students' Success Rate." In 2017 International Conference on Robots & Intelligent Systems (ICRIS). IEEE, 2017. http://dx.doi.org/10.1109/icris.2017.56.
Full textXu, Chengjie, Yuanyuan Zhang, and Bochao Xu. "Research of Construction Safety Factors Based on the Factor Analysis Method." In International Conference on Construction and Real Estate Management 2016. Reston, VA: American Society of Civil Engineers, 2017. http://dx.doi.org/10.1061/9780784480274.166.
Full textCali`, M., G. Orsello, M. Santarelli, and P. Leone. "Experimental Activity on the Tubular SOFC CHP100 kWe Field Unit in Italy: Factor Significance, Effects and Regression Model Analysis." In ASME 8th Biennial Conference on Engineering Systems Design and Analysis. ASMEDC, 2006. http://dx.doi.org/10.1115/esda2006-95802.
Full textLuo, Lu-xi, Ling-ying Tu, Xin-yu Cao, and Fang-fang Zhao. "Analysis of influencing factors on housing price in Chengdu based on factor-analysis method." In 2014 International Conference on Management Science and Engineering (ICMSE). IEEE, 2014. http://dx.doi.org/10.1109/icmse.2014.6930465.
Full textWang, Yaowu, Chongyang Wang, Nan Zhang, Yu Qin, and Zeng Li. "Analysis on Impact Factors of Real Estate Price Based on the Factor Analysis Method." In ICCREM 2015. Reston, VA: American Society of Civil Engineers, 2015. http://dx.doi.org/10.1061/9780784479377.089.
Full textReports on the topic "Factor Analysi"
Piatek, Rémi, Gabriella Conti, James Heckman, and Sylvia Frühwirth-Schnatter. Bayesian exploratory factor analysis. Cemmap, July 2014. http://dx.doi.org/10.1920/wp.cem.2014.3014.
Full textElectrotek Concepts. Industrial Power Factor Analysis Guidebook. Office of Scientific and Technical Information (OSTI), March 1995. http://dx.doi.org/10.2172/654078.
Full textGibbons, Robert D., Donald R. Hedeker, and R. D. Bock. Full-Information Item Bi-Factor Analysis. Fort Belvoir, VA: Defense Technical Information Center, July 1990. http://dx.doi.org/10.21236/ada229346.
Full textGuo, Xingzhou, Chi Tian, Jinwu Xiao, Yunfeng Chen, and Jiansong Zhang. Life Cycle Integration of Building Information Modeling in Infrastructure Projects. Purdue University, 2022. http://dx.doi.org/10.5703/1288284317356.
Full textM. Wasiolek. NOMINAL PERFORMANCE BIOSPHERE DOSE CONVERSION FACTOR ANALYSIS. Office of Scientific and Technical Information (OSTI), August 2005. http://dx.doi.org/10.2172/883410.
Full textWasiolek, M. A. Nominal Performance Biosphere Dose Conversion Factor Analysis. Office of Scientific and Technical Information (OSTI), July 2003. http://dx.doi.org/10.2172/836521.
Full textWasiolek, Maryla. Nominal Performance Biosphere Dose Conversion Factor Analysis. Office of Scientific and Technical Information (OSTI), December 2000. http://dx.doi.org/10.2172/837095.
Full textM. Wasiolek. Disruptive Event Biosphere Doser Conversion Factor Analysis. Office of Scientific and Technical Information (OSTI), December 2000. http://dx.doi.org/10.2172/837096.
Full textM. Wasiolek. Nominal Performance Biosphere Dose Conversion Factor Analysis. Office of Scientific and Technical Information (OSTI), September 2004. http://dx.doi.org/10.2172/838324.
Full textM. Wasiolek. Disruptive Event Biosphere Dose Conversion Factor Analysis. Office of Scientific and Technical Information (OSTI), September 2004. http://dx.doi.org/10.2172/838325.
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