Página 19 dos resultados de 4919 itens digitais encontrados em 0.011 segundos

## Measuring Forecasters' Perceptions of Inflation Persistence

Jain, MONICA
Fonte: Quens University Publicador: Quens University
EN; EN
Relevância na Pesquisa
26.66%
This dissertation presents a new measure of U.S. inflation persistence from the point of view of a professional forecaster. In chapter 2 I explore two different measures that give insight into the views of professional forecasters and link their views with U.S. inflation data. One of these measures, given by the persistence implied by forecast revisions, appears to have similarities with actual inflation persistence over the 1981–2008 sample period. Chapter 3 explores forecast revisions in a more general setting allowing forecasters to have their own views on inflation persistence as well as a unique information set. This chapter builds a measure of perceived inflation persistence via the implied autocorrelation function that follows from the estimates obtained using a forecaster-specific state-space model. When compared to the autocorrelation function for actual inflation, forecasters tend to react less to shocks that hit inflation than the actual inflation data would suggest. This could be due to increased credibility of the Federal Reserve, but it could also be a result of a bias in the underlying inflation forecasts. Chapter 4 focuses on this issue and finds that the reluctance of forecasters to make revisions to their previously announced forecasts causes their estimates of perceived inflation persistence to be understated as their announced inflation forecasts differ from their true inflation expectations. This chapter also presents a method to undo this bias by retrieving their true inflation expectations series.; Thesis (Ph.D...

## Proyección de demanda: ¡este problema no es normal!

Alonso Cifuentes, Julio César; Gallo Córdoba, Beatriz Eugenia
Tipo: article; Artículo Formato: pdf; 237-239 páginas; Digital
SPA
Relevância na Pesquisa
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El objetivo de este caso es discutir sobre la aproximación adecuada para realizar predicciones cuando se emplea un modelo de regresión lineal con una forma semilogarítmica. Para ello, se contextualiza el problema de una firma que requiere realizar predicciones sobre las cantidades demandadas de su producto estrella. De esta manera, el lector se enfrenta al desafío de cuestionar si una aproximación aparentemente intuitiva genera pronósticos adecuados.; This case discusses a problem that may arise when using a semi-logarithmic linear model to forecast the demand of a given product. This problem is presented using the discussion that emerges in a company that is looking for an approach to forecast the demand of its leading product. The reader faces the challenge of deciding which approach is adequate to the problem.

## Optimizing inventory levels using financial, lifecycle and forecast variance data

Hwang, Irene S
Fonte: Massachusetts Institute of Technology Publicador: Massachusetts Institute of Technology
Tipo: Tese de Doutorado Formato: 48 leaves
ENG
Relevância na Pesquisa
26.66%
Significant inventory write-offs have recently plagued ATI Technologies, a world leader in graphics and media processors. ATI's product-centric culture has long deterred attention from supply chain efficiency. Given that manufacturing lead time exceeds customer order lead time for its semiconductors, ATI relies heavily on their demand forecasting team to instigate supply chain activities. The PC business unit forecasting team translates market information into product-line forecast and also sets finished goods inventory levels intended to offset demand uncertainty. Today's inventory decisions are made in response to customer escalations, often ignoring financial implications. To add necessary rigor when setting these inventory levels, this thesis presents a model using wafer and unit cost, profit margin, product lifecycle stage and historical forecast error to categorize products into inventory risk levels. The resultant risk levels become a critical input to monthly demand-supply meetings with marketing, operations and senior executives - the outcome of which are wafer orders and assembly and test plans at the world's largest contract foundries and subcontractors. Finally, the 2006 acquisition of ATI by Advanced Micro Devices (AMD) offers unforeseen flexibility...

## Estudo empírico sobre as notas colocadas em circulação em Portugal

Fonte: Instituto Superior de Economia e Gestão Publicador: Instituto Superior de Economia e Gestão
Relevância na Pesquisa
26.66%
Mestrado em Econometria Aplicada e Previsão; Com a introdução do euro a análise do uso e circulação efetiva de notas por cada um dos países da zona euro passou a ser uma tarefa bastante desafiante devido à sua contínua migração entre países. É também cada vez mais importante a estimação e previsão da evolução da circulação de notas estando o DET encarregue de assegurar a emissão e a colocação em circulação da moeda legal necessária à economia nacional. O objetivo deste estudo é auxiliar o DET na sua tarefa e fazer um exercício comparativo da capacidade preditiva de um conjunto de modelos econométricos clássicos para prever a circulação de notas em Portugal, através de uma abordagem econométrica. Numa primeira fase é feita uma análise sobre a relação entre as notas em circulação e um conjunto de variáveis económicas através da abordagem VEC para o período entre 2002 e 2014. Os resultados demonstram evidência estatística de existência de uma relação de cointegração, havendo portanto uma relação de equilíbrio de longo prazo entre as variáveis. Numa segunda fase são testadas várias metodologias de previsão para avaliar qual o modelo com melhor desempenho para prever as notas em circulação. Tanto os três critérios para avaliar os erros de previsão como o teste Diebold Mariano apontaram para o método de Holt como aquele com melhor capacidade preditiva sobre as notas em circulação. Relativamente à previsão para o período de 2015 até 2017...

## Oceanic stochastic parametrizations in a seasonal forecast system

Andrejczuk, M.; Cooper, F. C.; Juricke, S.; Palmer, T. N.; Weisheimer, A.; Zanna, L.
Tipo: Artigo de Revista Científica
Relevância na Pesquisa
26.66%
We study the impact of three stochastic parametrizations in the ocean component of a coupled model, on forecast reliability over seasonal timescales. The relative impacts of these schemes upon the ocean mean state and ensemble spread are analyzed. The oceanic variability induced by the atmospheric forcing of the coupled system is, in most regions, the major source of ensemble spread. The largest impact on spread and bias came from the Stochastically Perturbed Parametrization Tendency (SPPT) scheme - which has proven particularly effective in the atmosphere. The key regions affected are eddy-active regions, namely the western boundary currents and the Southern Ocean. However, unlike its impact in the atmosphere, SPPT in the ocean did not result in a significant decrease in forecast error. Whilst there are good grounds for implementing stochastic schemes in ocean models, our results suggest that they will have to be more sophisticated. Some suggestions for next-generation stochastic schemes are made.; Comment: 24 pages, 3 figures

## Using Regression Kernels to Forecast A Failure to Appear in Court

Berk, Richard; Bleich, Justin; Kapelner, Adam; Henderson, Jaime; Barnes, Geoffrey; Kurtz, Ellen
Tipo: Artigo de Revista Científica
Relevância na Pesquisa
26.66%
Forecasts of prospective criminal behavior have long been an important feature of many criminal justice decisions. There is now substantial evidence that machine learning procedures will classify and forecast at least as well, and typically better, than logistic regression, which has to date dominated conventional practice. However, machine learning procedures are adaptive. They "learn" inductively from training data. As a result, they typically perform best with very large datasets. There is a need, therefore, for forecasting procedures with the promise of machine learning that will perform well with small to moderately-sized datasets. Kernel methods provide precisely that promise. In this paper, we offer an overview of kernel methods in regression settings and compare such a method, regularized with principle components, to stepwise logistic regression. We apply both to a timely and important criminal justice concern: a failure to appear (FTA) at court proceedings following an arraignment. A forecast of an FTA can be an important factor is a judge's decision to release a defendant while awaiting trial and can influence the conditions imposed on that release. Forecasting accuracy matters, and our kernel approach forecasts far more accurately than stepwise logistic regression. The methods developed here are implemented in the R package kernReg currently available on CRAN.; Comment: 43 pages...

## Forecast of the Chemical Aging and Relevant Color Changes in Painting

Zilbergleyt, B.
Tipo: Artigo de Revista Científica
Relevância na Pesquisa
26.66%
The article describes the potential application of thermodynamic simulation to forecast chemical aging and relevant color changes in painting. Qualitative and numerical results were obtained by applying the method to various mixtures of pigments without and with atmospheric components. The results were compared to the legendary recommendations on incompatible pigment mixtures with about an 80 percent match regarding potential color changes in the aged mixtures. Results for the cadmium yellow-lead white and cadmium lemon-emerald green mixtures are illustrated by pictures, gradually showing color changes caused by the aging. The method of thermodynamic simulation can be a powerful tool to investigate old masterpieces, in developing new materials, and to forecast some aspects of the aging of real masterpieces.; Comment: 7 pages, 3 tables, 2 figures

## MSSM Forecast for the LHC

Cabrera, Maria Eugenia; Casas, Alberto; de Austri, Roberto Ruiz
Tipo: Artigo de Revista Científica
Relevância na Pesquisa
26.66%
We perform a forecast of the MSSM with universal soft terms (CMSSM) for the LHC, based on an improved Bayesian analysis. We do not incorporate ad hoc measures of the fine-tuning to penalize unnatural possibilities: such penalization arises from the Bayesian analysis itself when the experimental value of $M_Z$ is considered. This allows to scan the whole parameter space, allowing arbitrarily large soft terms. Still the low-energy region is statistically favoured (even before including dark matter or g-2 constraints). Contrary to other studies, the results are almost unaffected by changing the upper limits taken for the soft terms. The results are also remarkable stable when using flat or logarithmic priors, a fact that arises from the larger statistical weight of the low-energy region in both cases. Then we incorporate all the important experimental constrains to the analysis, obtaining a map of the probability density of the MSSM parameter space, i.e. the forecast of the MSSM. Since not all the experimental information is equally robust, we perform separate analyses depending on the group of observables used. When only the most robust ones are used, the favoured region of the parameter space contains a significant portion outside the LHC reach. This effect gets reinforced if the Higgs mass is not close to its present experimental limit and persits when dark matter constraints are included. Only when the g-2 constraint (based on $e^+e^-$ data) is considered...

## The climate version of the Eta regional forecast model. 1. Evaluation of consistency between the Eta model and HadAM3P global model

Pisnichenko, I. A.; Tarasova, T. A.
Tipo: Artigo de Revista Científica
Relevância na Pesquisa
26.66%
The regional climate model prepared from Eta WS forecast model has been integrated over South America with the horizontal resolution of 40 km for the period of 1960-1990. The model was forced at its lateral boundaries by the outputs of HadAM3P. The data of HadAM3P represent simulation of modern climate with the resolution about 150 km. In order to prepare climate regional model from the Eta forecast model multiple modifications and corrections were made in the original model. The run of climate Eta model was made on the supercomputer SX-6. The detailed analysis of the results of dynamical downscaling experiment includes an investigation of a consistency between the regional and AGCM models as well as of ability of the regional model to resolve important features of climate fields on the finer scale than that resolved by AGCM. In this work the results of the investigation of a consistency between the output fields of the Eta model and HadAM3P are presented. The geopotential, temperature and wind fields of both models were analysed. For the evaluation of the likeness of these two models outputs,there were used Fourier analysis of time series, consistency index, constituted from linear regression coefficients, time mean and space mean models' arithmetic difference and root mean square difference...

## Parameter uncertainty in forecast recalibration

Siegert, Stefan; Sansom, Philip G.; Williams, Robin
Tipo: Artigo de Revista Científica
Relevância na Pesquisa
26.66%
Ensemble forecasts of weather and climate are subject to systematic biases in the ensemble mean and variance, leading to inaccurate estimates of the forecast mean and variance. To address these biases, ensemble forecasts are post-processed using statistical recalibration frameworks. These frameworks often specify parametric probability distributions for the verifying observations. A common choice is the Normal distribution with mean and variance specified by linear functions of the ensemble mean and variance. The parameters of the recalibration framework are estimated from historical archives of forecasts and verifying observations. Often there are relatively few forecasts and observations available for parameter estimation, and so the fitted parameters are also subject to uncertainty. This artefact is usually ignored. This study reviews analytic results that account for parameter uncertainty in the widely used Model Output Statistics recalibration framework. The predictive bootstrap is used to approximate the parameter uncertainty by resampling in more general frameworks such as Non-homogeneous Gaussian Regression. Forecasts on daily, seasonal and annual time scales are used to demonstrate that accounting for parameter uncertainty in the recalibrated predictive distributions leads to probability forecasts that are more skilful and reliable than those in which parameter uncertainty is ignored. The improvements are attributed to more reliable tail probabilities of the recalibrated forecast distributions.; Comment: 22 pages...

## Forecast and event control: On what is and what cannot be possible

Svozil, Karl
Tipo: Artigo de Revista Científica
Relevância na Pesquisa
26.66%
Consequences of the basic and most evident consistency requirement-that measured events cannot happen and not happen at the same time-are shortly reviewed. Particular emphasis is given to event forecast and event control. As a consequence, particular, very general bounds on the forecast and control of events within the known laws of physics are derived. These bounds are of a global, statistical nature and need not affect singular events or groups of events.; Comment: Paper presented on the Workshop on "Determinism" at Ringberg Castle, Germany, July 6th, 2001

## A new method for choosing parameters in delay reconstruction-based forecast strategies

Garland, Joshua; James, Ryan G.; Bradley, Elizabeth
Tipo: Artigo de Revista Científica
Relevância na Pesquisa
26.66%
Delay-coordinate reconstruction is a proven modeling strategy for building effective forecasts of nonlinear time series. The first step in this process is the estimation of good values for two parameters, the time delay and the embedding dimension. Many heuristics and strategies have been proposed in the literature for estimating these values. Few, if any, of these methods were developed with forecasting in mind, however, and their results are not optimal for that purpose. Even so, these heuristics---intended for other applications---are routinely used when building delay coordinate reconstruction-based forecast models. In this paper, we propose a new strategy for choosing optimal parameter values for forecast methods that are based on delay-coordinate reconstructions. The basic calculation involves maximizing the shared information between each delay vector and the future state of the system. We illustrate the effectiveness of this method on several synthetic and experimental systems, showing that this metric can be calculated quickly and reliably from a relatively short time series, and that it provides a direct indication of how well a near-neighbor based forecasting method will work on a given delay reconstruction of that time series. This allows a practitioner to choose reconstruction parameters that avoid any pathologies...

## Planetary Kp index forecast using autoregressive models

Gonzalez, Arian Ojeda; Denardini, Clezio Marcos; Odriozola, Siomel Savio; Rosa, Reinaldo Roberto; Mendes Jr, Odim
Tipo: Artigo de Revista Científica
Relevância na Pesquisa
26.66%
The geomagnetic Kp index is derived from the K index measurements obtained from thirteen stations located around the Earth geomagnetic latitudes between $48^\circ$ and $63^\circ$. This index is processed every three hours, is quasi-logarithmic and estimates the geomagnetic activity. The Kp values fall within a range of 0 to 9 and are organized as a set of 28 discrete values. The data set is important because it is used as one of the many input parameters of magnetospheric and ionospheric models. The objective of this work is to use historical data from the Kp index to develop a methodology to make a prediction in a time interval of at least three hours. Five different models to forecast geomagnetic indices Kp and ap are tested. Time series of values of Kp index from 1932 to 15/12/2012 at 21:00 UT are used as input to the models. The purpose of the model is to predict the three measured values after the last measured value of the Kp index (it means the next 9 hours values). The AR model provides the lowest computational cost with satisfactory results. The ARIMA model is efficient for predicting Kp index during geomagnetic disturbance conditions. This paper provides a quick and efficient way to make a prediction of Kp index, without using satellite data. Although it is reported that the forecast results are better when satellite data are used. In the literature we find that the linear correlation between predicted values and actual values is $77\%$...

## The extended Baryon Oscillation Spectroscopic Survey (eBOSS): a cosmological forecast

Zhao, Gong-Bo; Wang, Yuting; Ross, Ashley J.; Shandera, Sarah; Percival, Will J.; Dawson, Kyle S.; Kneib, Jean-Paul; Myers, Adam D.; Brownstein, Joel R.; Comparat, Johan; Delubac, Timothée; Gao, Pengyuan; Hojjati, Alireza; Koyama, Kazuya; McBride, Camero
Tipo: Artigo de Revista Científica
Relevância na Pesquisa
26.66%

## MOSE: optical turbulence and atmospherical parameters operational forecast at ESO ground-based sites. II: atmospherical parameters in the surface layer [0-30] m

Lascaux, Franck; Masciadri, Elena; Fini, Luca
Tipo: Artigo de Revista Científica
Relevância na Pesquisa
26.66%
This article is the second of a series of articles aiming at proving the feasibility of the forecast of all the most relevant classical atmospherical parameters for astronomical applications (wind speed and direction, temperature, relative humidity) and the optical turbulence (Cn2 and the derived astro-climatic parameters like seeing, isoplanatic angle, wavefront coherence time...). This study is done in the framework of the MOSE project, and focused above the two ESO ground-bases sites of Cerro Paranal and Cerro Armazones. In this paper we present the results related to the Meso-Nh model ability in reconstructing the surface layer atmospherical parameters (wind speed intensity, wind direction and absolute temperature, [0-30] m a.g.l.). The model reconstruction of all the atmospherical parameters in the surface layer is very satisfactory. For the temperature, at all levels, the RMSE (Root Mean Square Error) is inferior to 1{\deg}C. For the wind speed, it is ~2 m/s, and for the wind direction, it is in the range [38-46{\deg}], at all levels, that corresponds to a RMSE_relative in a range [21-26{\deg}]. If a filter is applied for the wind direction (the winds inferior to 3 m/s are discarded from the computations), the wind direction RMSE is in the range [30-41{\deg}]...

## MOSE: optical turbulence and atmospherical parameters operational forecast at ESO ground-based sites. I: Overview and atmospherical parameters vertical stratification on [0-20] km

Masciadri, E.; Lascaux, F.; Fini, L.
Tipo: Artigo de Revista Científica