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Identifying preschool measures most predictive of language outcomes at 11 years in the Early Language in Victoria Study ...
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A Classification Analysis of the High and Low Levels of Global Competence of Secondary Students: Insights from 25 Countries/Regions
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In: Sustainability ; Volume 13 ; Issue 19 (2021)
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On the Efficiency of German Growth Forecasts: An Empirical Analysis Using Quantile Random Forests ...
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Abstract:
We use quantile random forests (QRF) to study the efficiency of the growth forecasts published by three leading German economic research institutes for the sample period from 1970 to 2017. To this end, we use a large array of predictors, including topics extracted by means of computational-linguistics tools from the business-cycle reports of the institutes, to model the information set of the institutes. We use this array of predictors to estimate the quantiles of the conditional distribution of the forecast errors made by the institutes, and then fit a skewed t-distribution to the estimated quantiles. We use the resulting density forecasts to compute the log probability score of the predicted forecast errors. Based on an extensive insample and out-of-sample analysis, we find evidence, particularly in the case of longer-term forecasts, against the null hypothesis of strongly efficient forecasts. We cannot reject weak efficiency of forecasts. ...
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Keyword:
330 Wirtschaft; Density forecasts; Forecast efficiency; Growth forecasts; Quantile-random forests
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URL: https://dx.doi.org/10.18452/21910 https://edoc.hu-berlin.de/handle/18452/22627
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On the Efficiency of German Growth Forecasts: An Empirical Analysis Using Quantile Random Forests
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Growing Random Forests reveals that exposure and proficiency best account for 2 individual variability in L2 (and L1) brain potentials for syntax and semantics
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On the efficiency of German growth forecasts: An empirical analysis using quantile random forests
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Verbing and nouning in French : toward an ecologically valid approach to sentence processing
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Automatic Selection of Parallel Data for Machine Translation
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In: IFIP Advances in Information and Communication Technology ; 14th IFIP International Conference on Artificial Intelligence Applications and Innovations (AIAI) ; https://hal.inria.fr/hal-01821299 ; 14th IFIP International Conference on Artificial Intelligence Applications and Innovations (AIAI), May 2018, Rhodes, Greece. pp.146-156, ⟨10.1007/978-3-319-92016-0_14⟩ (2018)
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Furosine and HMF determination in prebiotic-supplemented infant formula from Spanish market
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Modelling the interplay of multiple cues in prosodic focus marking
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In: Laboratory Phonology: Journal of the Association for Laboratory Phonology; Vol 8, No 1 (2017); 4 ; 1868-6354 (2017)
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Predictive modeling of human placement decisions in an English Writing Placement Test
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In: Graduate Theses and Dissertations (2016)
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To HAVE and to BE: Function Word Reduction in Child Speech, Child Directed Speech and Inter-adult Speech
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Modelling phonetic reduction in a corpus of spoken English using Random Forests and Mixed-Effects Regression
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Dilts, Philip C. - : University of Alberta. Department of Linguistics., 2013
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Modelling phonetic reduction in a corpus of spoken English using Random Forests and Mixed-Effects Regression
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Dilts, Philip C. - : University of Alberta. Department of Linguistics., 2013
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A random forest system combination approach for error detection in digital dictionaries
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A Hybrid approach for biomedical relation extraction using finite state automata and random forest-weighted fusion
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