Fitting the mortality models and making forecasts
llc: a collection of R functions for fitting a class of Lee-Carter mortality models using iterative fitting algorithms
... This generalised modelling methodology is implemented within the R statistical software in the form of a specialised set of command functions that apply the above mentioned iterative fitting method. The package ...
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Stochastic population forecasts using functional data models for mortality, fertility and migration
... data models for mortality, fertility and migration Abstract: Age-sex-specific population forecasts are derived through stochastic population re- newal using forecasts of mortality, ...
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Fitting Models of Vulnerability to Toxicity with Generalized Linear Models
... regression models that allow the mean to depend on the explanatory variables through a link function ...to mortality and when ‘experimental units’ are just ‘screened’ for vulnerability to ...for ...
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Evaluation of simple methods for regional mortality forecasts
... in mortality will have some ...in mortality would probably result in the SMR Scaling method generating lower forecast errors overall, with all age-specific death rates lying within the plausible ...regional ...
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Forecasts of COPD mortality in Australia: 2006-2025
... COPD mortality rates as a function of age (taken to be the midpoint of the age ...and mortality for each year, and define these as mortality-age ...COPD mortality and use functional data ...
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Decoder Fitting for OO Gauge Models
... price, making the independent and flexible control of a model railway ...by making adjustments to the decoder settings called configuration variables or ...
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Common mortality modeling and coherent forecasts. An empirical analysis of worldwide mortality data
... West-cluster mortality experience for the time period 1960-2006 for fitting the models, we need to refer to as long a mortality history as possible, in order to produce viable long term ...
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Common mortality modelling and coherent forecasts. An empirical analysis of worldwide mortality data
... West-cluster mortality experience for the time period 1960-2006 for fitting the models, we need to refer to as long a mortality history as possible, in order to produce viable long term ...
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Fitting multiplicative models by robust alternating regressions.
... infant mortality rate (inf mort), number of inhabitants per physician (inhab/doc), daily calorie consumption per head (calorie), and proportion of babies with underweight at birth in % (baby ...
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An R package for fitting age, period and cohort models
... issue making APC models complicated to treat is that age, period and cohort are not ...and mortality rates in term of either period and/or cohort effects in the general multiplicative risk model, ...
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Probability Distribution Fitting to Maternal Mortality in Nigeria
... Maternal Mortality (MM) cannot be ...maternal mortality rates (MMR) in Nigeria, identify some fitted distributions to MMR and determine which of the distributions best fits the ...
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Density Forecasts with MIDAS Models
... sity forecasts. First, we compute density forecasts from different MIDAS models, the classical MIDAS models and the unrestricted version, ...of models when accounting for parameter ...
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Robust fitting of mixture regression models
... Similar to the least squares estimate (LSE) for linear regression, the normality based MLE is sensitive to outliers or heavy-tailed error distributions. For linear regression, the M estimate, which replaces the least ...
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affyplm: Fitting Probe Level Models
... max.its controls the maximum number of iterations of IRLS that will be used in the model fitting procedure. By default max.its=20 . Note, that this many iterations may not be needed if convergence occurs. ...
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Fitting Data with Different Error Models »
... It can be seen that (in the case of Gaussian-type measurement noise) only the type of the error model determines the parameter values, since we should always minimize the least squares of the errors. There are different ...
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Fitting State Space Models with EViews
... homoscedasticity and normality (based on Commandeur and Koopman 2007 , p. 90–96). Results are summarized in Table 1 . They indicate that all of the model assumptions are satisfied. Although EViews allows storing all ...
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Time-varying Models for Macroeconomic Forecasts
... in models has em- pirical ...in models, and specifications of SV and time-varying parameters with VARs were examined in estimation and forecasting exercises in dif- ferent macroeconomic ...of models ...
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Models and forecasts of credit card balance
... Statistical Models We consider alternative explanatory models for credit card ...regression models, mixture regression and panel regression ...allows forecasts l periods ...
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Combining forecasts from nested models
... Keywords: Forecast combination, predictability, forecast evaluation JEL classification: C53, C52 *Clark (corresponding author): Economic Research Dept.; Federal Reserve Bank of Kansas City; 925 Grand; Kansas City, MO ...
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