scholarly journals Performance of Recent Multimodel ENSO Forecasts

2012 ◽  
Vol 51 (3) ◽  
pp. 637-654 ◽  
Author(s):  
Michael K. Tippett ◽  
Anthony G. Barnston ◽  
Shuhua Li
Keyword(s):  
Statistical Models ◽  
Lead Time ◽  
Forecast Error ◽  
Error Variance ◽  
Multiple Model ◽  
Dynamical Models ◽  
Additional Information ◽  
Spring Predictability Barrier ◽  
International Research Institute ◽  
The Mean

AbstractThe performance of the International Research Institute for Climate and Society “ENSO forecast plume” during the 2002–11 period is evaluated using deterministic and probabilistic verification measures. The plume includes multiple model forecasts of the Niño-3.4 index for nine overlapping 3-month periods beginning the month following the latest observations. Skills decrease with increasing lead time and are highest for forecasts made after the northern spring predictability barrier for target seasons occurring prior to the forthcoming such barrier. Forecasts are found to verify systematically better against observations occurring earlier than the intended forecast targets, an effect that becomes greater with increasing lead time. During the study period, the mean forecasts of dynamical models appear to slightly (and statistically insignificantly) outperform those of statistical models, representing a subtle shift from earlier studies. The mean forecasts of dynamical models have overall larger anomalies but similar errors to those of statistical models. Intermodel spread is related to forecast error in an average sense with changes in forecast error due to changes in lead and verification season being properly reflected in changes in spread. The intermodel spread underestimates the forecast error variance, to a greater extent for statistical forecasts than for dynamical ones. Year-to-year changes in plume spread provide little additional information relative to climatological ones.

scholarly journals Hydrologic Forecasts Verification and Comparison of Forecasting Methods

2018 ◽  
Author(s):  
Sergei Borsch ◽  
Andrei Khristoforov ◽  
Vladimir Krovotynzev ◽  
Ekaterina Leontieva ◽  
Yuri Simonov ◽  
...  
Keyword(s):  
Error Estimation ◽  
Lead Time ◽  
Statistical Tests ◽  
Forecast Error ◽  
Mean Square ◽  
Forecasting Methods ◽  
Forecasting Method ◽  
Efficiency Estimation ◽  
Hydrologic Characteristic ◽  
The Mean

This paper presents the methods of estimating the mean square error of hydrological forecasts, allowing for assessment of their practical applicability. Depending upon the amount and composition of available hydrometeorological data, an appropriate method for forecast error estimation is chosen. A system of statistical tests for comparison of different forecasting methods for the same hydrologic characteristic with the same lead time is presented. These tests allow for choosing an optimal and most accurate forecasting method. Hydrological forecasting method efficiency estimation is based on comparing the forecast error with climatology or inertial (persistence) forecast error using presented tests.

scholarly journals Improved Visual Localization via Graph Filtering

2021 ◽  
Vol 7 (2) ◽  
pp. 20
Author(s):  
Carlos Lassance ◽  
Yasir Latif ◽  
Ravi Garg ◽  
Vincent Gripon ◽  
Ian Reid
Keyword(s):  
Image Retrieval ◽  
Large Scale ◽  
Visual Localization ◽  
Localization Accuracy ◽  
Additional Information ◽  
Feature Representations ◽  
The Mean ◽  
Classical Image ◽  
Vision Based Localization ◽  
Improve Reliability

Vision-based localization is the problem of inferring the pose of the camera given a single image. One commonly used approach relies on image retrieval where the query input is compared against a database of localized support examples and its pose is inferred with the help of the retrieved items. This assumes that images taken from the same places consist of the same landmarks and thus would have similar feature representations. These representations can learn to be robust to different variations in capture conditions like time of the day or weather. In this work, we introduce a framework which aims at enhancing the performance of such retrieval-based localization methods. It consists in taking into account additional information available, such as GPS coordinates or temporal proximity in the acquisition of the images. More precisely, our method consists in constructing a graph based on this additional information that is later used to improve reliability of the retrieval process by filtering the feature representations of support and/or query images. We show that the proposed method is able to significantly improve the localization accuracy on two large scale datasets, as well as the mean average precision in classical image retrieval scenarios.

Explanation Plus Prediction—The Logical Focus of Project Management Research

2021 ◽  
pp. 875697282199994
Author(s):  
Joseph F. Hair ◽  
Marko Sarstedt
Keyword(s):  
Project Management ◽  
Statistical Models ◽  
Predictive Power ◽  
Mean Absolute Error ◽  
Explanatory Power ◽  
Absolute Error ◽  
Model Parameters ◽  
Mean Square ◽  
Management Research ◽  
The Mean

Most project management research focuses almost exclusively on explanatory analyses. Evaluation of the explanatory power of statistical models is generally based on F-type statistics and the R 2 metric, followed by an assessment of the model parameters (e.g., beta coefficients) in terms of their significance, size, and direction. However, these measures are not indicative of a model’s predictive power, which is central for deriving managerial recommendations. We recommend that project management researchers routinely use additional metrics, such as the mean absolute error or the root mean square error, to accurately quantify their statistical models’ predictive power.

The influence of economic policy uncertainty and geopolitical risk on US citizens overseas air passenger travel by regional destination

2020 ◽  
pp. 135481662098119
Author(s):  
James E Payne ◽  
Nicholas Apergis
Keyword(s):  
Economic Policy ◽  
Forecast Error ◽  
Error Variance ◽  
Variance Decomposition ◽  
Air Travel ◽  
Policy Uncertainty ◽  
Economic Policy Uncertainty ◽  
Passenger Travel ◽  
Forecast Error Variance

This research note extends the literature on the role of economic policy uncertainty and geopolitical risk on US citizens overseas air travel through the examination of the forecast error variance decomposition of total overseas air travel and by regional destination. Our empirical findings indicate that across regional destinations, US economic policy uncertainty explains more of the forecast error variance of US overseas air travel, followed by geopolitical risk with global economic policy uncertainty explaining a much smaller percentage of the forecast error variance.

scholarly journals Predicting Water Availability in Water Bodies under the Influence of Precipitation and Water Management Actions Using VAR/VECM/LSTM

Climate ◽  
2021 ◽  
Vol 9 (9) ◽  
pp. 144
Author(s):  
Harleen Kaur ◽  
Mohammad Afshar Alam ◽  
Saleha Mariyam ◽  
Bhavya Alankar ◽  
Ritu Chauhan ◽  
...  
Keyword(s):  
Water Management ◽  
Short Term Memory ◽  
Forecast Error ◽  
Error Variance ◽  
Water Levels ◽  
Water Bodies ◽  
Economic Activities ◽  
Management Actions ◽  
Forecast Error Variance ◽  
Water Treatments

Recently, awareness about the significance of water management has risen as population growth and global warming increase, and economic activities and land use continue to stress our water resources. In addition, global water sustenance efforts are crippled by capital-intensive water treatments and water reclamation projects. In this paper, a study of water bodies to predict the amount of water in each water body using identifiable unique features and to assess the behavior of these features on others in the event of shock was undertaken. A comparative study, using a parametric model, was conducted among Vector Autoregression (VAR), the Vector Error Correction Model (VECM), and the Long Short-Term Memory (LSTM) model for determining the change in water level and water flow of water bodies. Besides, orthogonalized impulse responses (OIR) and forecast error variance decompositions (FEVD) explaining the evolution of water levels and flow rates, the study shows the significance of VAR/VECM models over LSTM. It was found that on some water bodies, the VAR model gave reliable results. In contrast, water bodies such as water springs gave mixed results of VAR/VECM.

A note on reduction of the number of parameters in linear statistical models

2012 ◽  
Vol 62 (1) ◽  
Author(s):  
Lubomír Kubáček
Keyword(s):  
Statistical Analysis ◽  
Linear Model ◽  
Covariance Matrix ◽  
Statistical Models ◽  
Approximate Model ◽  
Model Matrix ◽  
The Mean ◽  
Linear Statistical Models

AbstractIn certain settings the mean response is modeled by a linear model using a large number of parameters. Sometimes it is desirable to reduce the number of parameters prior to conducting the experiment and prior to the actual statistical analysis. Essentially, it means to formulate a simpler approximate model to the original “ideal” one. The goal is to find conditions (on the model matrix and covariance matrix) under which the reduction does not influence essentially the data fit. Here we try to develop such conditions in regular linear model without and with linear restraints. We emphasize that these conditions are independent of observed data.

scholarly journals Oil Prices and the U.S. Dollar Exchange Rate: Evidence from the Monetary Model

2018 ◽  
Vol 10 (4) ◽  
pp. 17
Author(s):  
Moayad H. Al Rasasi
Keyword(s):  
Exchange Rate ◽  
Forecast Error ◽  
Negative Relationship ◽  
Impulse Response Function ◽  
Decomposition Analysis ◽  
Oil Prices ◽  
Error Variance ◽  
Monetary Model ◽  
Forecast Error Variance ◽  
Positive Shock

This paper analyzes how changes in global oil prices affect the US dollar (USD) exchange rate based on the monetary model of exchange rate. We find evidence indicating a negative relationship between oil prices and the USD exchange rate against 12 currencies. Specifically, the analysis of the impulse response function shows that the depreciation rate of the USD exchange rate ranges between 0.002 and 0.018 percentage points as a result of a one-standard deviation positive shock to the real price of crude oil. In the same vein, the forecast error variance decomposition analysis reveals that variation in the USD exchange rate is largely attributable to changes in the price of oil rather than monetary fundamentals. In last, the out-of-sample forecast exercise indicates that oil prices enhance the predictability power of the monetary model of exchange rate.

Rings of Uranus: A Review of Occultation Results

1982 ◽  
Vol 60 ◽  
pp. 237-256 ◽  
Author(s):  
James L. Elliot
Keyword(s):  
Spatial Resolution ◽  
Particle Collisions ◽  
Dynamical Models ◽  
High Resolution Data ◽  
Unique System ◽  
Structural Details ◽  
The Mean ◽  
Geometric Albedo ◽  
Resolution Data ◽  
Better Than

Since their discovery in 1977 (Elliot 1979), the dark, narrow rings of Uranus have intrigued dynamicists. The main enigma has been how the rings can remain so narrow - only a few km wide - when particle collisions and the Poynting-Robertson effect should cause the particles to disperse. The Uranian rings have posed other problems as well, and have proved to be a unique system for developing dynamical models of rings. The reason for this theoretical interest is the high precision and time coverage of the data available from occultation observations. With occultations we obtain a spatial resolution of 1 km in the position of ring segments and a resolution of 4 km in their structural details. These high-resolution data are available sufficiently often to be useful for dynamical purposes - at the rate of 1-2 events per year. This spatial resolution is somewhat better than that obtained by Voyager imaging of Jupiter’s and Saturn’s rings (Owen et al. 1979; Smith et al. 1981). Ground-based images of the Uranian rings, obtained by Matthews, Nicholson, and Neugebauer (1981), have a spatial resolution of ~50,000 km. Although unable to resolve individual rings, these data have established the mean geometric albedo of the rings at 0.030 ± 0.005.

scholarly journals KAJIAN AKTIVITAS EKONOMI LUAR NEGERI INDONESIA TERHADAP PERTUMBUHAN EKONOMI INDONESIA PERIODE 1998-2014

2017 ◽  
Vol 9 (2) ◽  
pp. 119
Author(s):  
Ryan Hawari ◽  
Fitri Kartiasih
Keyword(s):  
Economic Growth ◽  
Foreign Direct Investment ◽  
Exchange Rate ◽  
Direct Investment ◽  
Forecast Error ◽  
Foreign Debt ◽  
Trade Openness ◽  
Impulse Response Function ◽  
Error Variance ◽  
Forecast Error Variance

Indonesia is a developing country which adopts an “open economic”. That caused Indonesia economic is strongly influenced by factors that come from outside of Indonesia. External factors in this research is referred to foreign debt, foreign direct investment, trade openness and exchange rate of rupiah with USD. The analytical method in this research used Vector Error Correction Model (VECM) which will focused on Impulse Response Function (IRF) and Forecast Error Variance Decomposition (FEVD). Based on result of IRF, exchange rate had a positive effect to economic growth, while foreign debt, foreign direct investment and trade openness had a negative effect to economic growth. Based on result of FEVD, shock on economic growth in Indonesia affected by economic growth itself (43.21%), followed by foreign debt (26.30%), trade openness (14.16%), foreign direct investment (8.29%) and exchange rate (8.04%) Keywords: economic growth, trade openness, VECM, IRF, FEVD

On the realizability of pressure–strain closures

2014 ◽  
Vol 755 ◽  
pp. 535-560 ◽  
Author(s):  
Aashwin A. Mishra ◽  
Sharath S. Girimaji
Keyword(s):  
Statistical Models ◽  
Flow Stability ◽  
Mean Flow ◽  
Model Formulation ◽  
Closure Model ◽  
Two Component ◽  
The Mean ◽  
The Relationship ◽  
Rapid Pressure ◽  
Domain Of Validity

AbstractThe realizability condition for statistical models of turbulence is augmented to ensure that not only is the Reynolds stress tensor positive semi-definite, but the process of its evolution is physically attainable as well. The mathematical constraints due to this process realizability requirement on the rapid pressure strain correlation are derived. The resulting constraints reveal important limits on the inter-component energy transfer and the consequent flow stability characteristics, as a function of the mean flow. For planar mean flows, the realizability constraints are most stringent for the case of purely sheared flows rather than elliptic flows. The relationship between the constraints and flow stability is explained. Process realizability leads to closure model guidance not only at the two-component (2C) limit of turbulence (as in the classical realizability approach) but throughout the anisotropy space. Consequently, the domain of validity and applicability of current models can be clearly identified for different mean flows. A simple framework for incorporating these process realizability constraints in model formulation is outlined.

Sign in / Sign up

Export Citation Format

Share Document