浅滩
发表于 2025-3-28 17:06:43
Emery Balint M.C.E.(Melb.), M.I.C.E.eneral these models fall into three categories, Exponentially Weighted Moving Average models, Generalized Autoregressive Conditional Hetroscedasticity models, and Stochastic Volatility Differential Equations. In this chapter we introduce the first two of these modeling approaches.
教义
发表于 2025-3-28 21:07:48
Inferential Statistical Methods for Energy Risk Managers population values or it may indicate that the conjecture is untenable. Hypothesis testing is a formal mechanism by which we can make and test inferential statements about the characteristics of a population. It uses the information contained in a sample to assess the validity of a conjecture about a specific population parameter.
dandruff
发表于 2025-3-29 00:11:27
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陈列
发表于 2025-3-29 04:11:14
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dowagers-hump
发表于 2025-3-29 10:06:02
Descriptive Statistics of Energy Prices and Returnsstics is to reduce the original sample into a handful of more understandable metrics without distorting or losing too much of the valuable information contained in the individual observations. We begin by collecting . observations {.., ..,…,..} on the price return random variable .. These measuremen
lanugo
发表于 2025-3-29 15:28:41
Inferential Statistical Methods for Energy Risk Managerscollected from a sample. Such generalizations are about an unobserved population. A population consists of all values (past and future) of the random variable of interest. In most circumstances the exact value of a population parameter such as the mean or variance will be unknown, and we will have t
贵族
发表于 2025-3-29 18:53:27
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滔滔不绝地讲
发表于 2025-3-29 20:36:57
Correlation Analysisor characteristic of a sample. Another important element of applied statistical modeling of energy risks concerns the relationship between two or more price or other variables. Generally, a risk manager will be interested in whether above (below) average values of one variable tend to be associated
聪明
发表于 2025-3-30 01:21:13
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multiply
发表于 2025-3-30 04:48:37
Multiple Regression and Predictionct more than one independent variable to influence the dependent variable. It allows us to explore the relationship between several independent and a single dependent variable. We also discuss multivariate regression which arises when we have several dependent variables dependent on the same (or som