NumXL - AbsoluteAstronomy.com

NumXL is an econometrics/time series analysis add-in for Microsoft Excel

Microsoft Excel

Microsoft Excel is a proprietary commercial spreadsheet application written and distributed by Microsoft for Microsoft Windows and Mac OS X. It features calculation, graphing tools, pivot tables, and a macro programming language called Visual Basic for Applications...

. Developed by Spider Financial, NumXL provides a wide variety of statistical and time series analysis techniques, including linear and nonlinear time series modeling, statistical tests and others.

Although NumXL is intended as an analytical Add-in for Excel, it extends the Excel’s user-interface, and offers numerous wizards, menu and toolbar to automate the mundane phases of time series analysis: summary statistics, test of hypothesis, correlogram analysis, modeling , calibration, residuals diagnosis, back-testing and forecast.

NumXL users come from various backgrounds of finance, economics, engineering and science. NumXL is used in academic and research institutions as well as industrial enterprises.

NumXL User's Interface

NumXL comes with an elaborate user-interface (i.e. menu and toolbar), and interactive wizards to improve the general usability of the software. The NumXL UI components automate the common process/steps of a time series analysis and modeling.

Using the UI components and the wizards, the user specifies the time series of interest, fine-tune the desired analysis options and specify the location on his/her worksheet for the output. NumXL generates the corresponding analysis blocks (with underlying formulas) in the designated location

Statistical Testing

Hypothesis Test for population mean, for standard deviation, for skewness
Skewness
In probability theory and statistics, skewness is a measure of the asymmetry of the probability distribution of a real-valued random variable. The skewness value can be positive or negative, or even undefined...

and for excess kurtosis.
Normality test
Normality test
In statistics, normality tests are used to determine whether a data set is well-modeled by a normal distribution or not, or to compute how likely an underlying random variable is to be normally distributed....

using Jarque–Bera test
Jarque–Bera test
In statistics, the Jarque–Bera test is a goodness-of-fit test of whether sample data have the skewness and kurtosis matching a normal distribution. The test is named after Carlos Jarque and Anil K. Bera...

, Shapiro–Wilk test, and Chi-square test methods.
White-noise test - Serial correlation tests (Portmanteau Test
Portmanteau test
A portmanteau test is a type of statistical hypothesis test in which the null hypothesis is well specified, but the alternative hypothesis is more loosely specified. Tests constructed in this context can have the property of being at least moderately powerful against a wide range of departures from...

, Ljung-Box test
Ljung-Box test
The Ljung–Box test is a type of statistical test of whether any of a group of autocorrelations of a time series are different from zero...

and modified Q-test).
Autoregressive Conditional Heteroskedasticity (ARCH)
Autoregressive conditional heteroskedasticity
In econometrics, AutoRegressive Conditional Heteroskedasticity models are used to characterize and model observed time series. They are used whenever there is reason to believe that, at any point in a series, the terms will have a characteristic size, or variance...

effect test.

Linear Time Series

Basic Operators - DIFF, LAG, WMA, Add, Subtract, scale, and time-reverse operators.
Autocorrelation function(ACF)
Autocorrelation
Autocorrelation is the cross-correlation of a signal with itself. Informally, it is the similarity between observations as a function of the time separation between them...

and Partial autocorrelation function (PACF)
Partial autocorrelation function
In time series analysis, the partial autocorrelation function plays an important role in data analyses aimed at identifying the extent of the lag in an autoregressive model...

.
Cross-correlation functions
Cross-correlation
In signal processing, cross-correlation is a measure of similarity of two waveforms as a function of a time-lag applied to one of them. This is also known as a sliding dot product or sliding inner-product. It is commonly used for searching a long-duration signal for a shorter, known feature...

- XCF and EWXCF
Autoregressive Moving Average (ARMA) model
Autoregressive moving average model
In statistics and signal processing, autoregressive–moving-average models, sometimes called Box–Jenkins models after the iterative Box–Jenkins methodology usually used to estimate them, are typically applied to autocorrelated time series data.Given a time series of data Xt, the ARMA model is a...
AirLine Model
Generalized Linear Model (GLM)
Generalized linear model
In statistics, the generalized linear model is a flexible generalization of ordinary linear regression. The GLM generalizes linear regression by allowing the linear model to be related to the response variable via a link function and by allowing the magnitude of the variance of each measurement to...
Goodness of fit
Goodness of fit
The goodness of fit of a statistical model describes how well it fits a set of observations. Measures of goodness of fit typically summarize the discrepancy between observed values and the values expected under the model in question. Such measures can be used in statistical hypothesis testing, e.g...

- LLF
Likelihood function
In statistics, a likelihood function is a function of the parameters of a statistical model, defined as follows: the likelihood of a set of parameter values given some observed outcomes is equal to the probability of those observed outcomes given those parameter values...

, AICc
Akaike information criterion
The Akaike information criterion is a measure of the relative goodness of fit of a statistical model. It was developed by Hirotsugu Akaike, under the name of "an information criterion" , and was first published by Akaike in 1974...

and model's diagnosis.
Forecast and back-testing

ARCH/GARCH Analysis

Basic Operators - EWMA/EWV
GARCH Model.
Exponential GARCH (E-GARCH) Model.
GARCH in the mean (GARCH-M) Model.
Support for Gaussian, Student's t and GED distributed innovations/shocks.
Goodness of fit
Goodness of fit
The goodness of fit of a statistical model describes how well it fits a set of observations. Measures of goodness of fit typically summarize the discrepancy between observed values and the values expected under the model in question. Such measures can be used in statistical hypothesis testing, e.g...

- LLF
Likelihood function
In statistics, a likelihood function is a function of the parameters of a statistical model, defined as follows: the likelihood of a set of parameter values given some observed outcomes is equal to the probability of those observed outcomes given those parameter values...

, AICc
Akaike information criterion
The Akaike information criterion is a measure of the relative goodness of fit of a statistical model. It was developed by Hirotsugu Akaike, under the name of "an information criterion" , and was first published by Akaike in 1974...

and model's diagnosis

Advanced (Combo) Models

Model Definition Function.
Mixed Model - likelihood function
Likelihood function
In statistics, a likelihood function is a function of the parameters of a statistical model, defined as follows: the likelihood of a set of parameter values given some observed outcomes is equal to the probability of those observed outcomes given those parameter values...

.
Goodness of fit
Goodness of fit
The goodness of fit of a statistical model describes how well it fits a set of observations. Measures of goodness of fit typically summarize the discrepancy between observed values and the values expected under the model in question. Such measures can be used in statistical hypothesis testing, e.g...

- LLF
Likelihood function
In statistics, a likelihood function is a function of the parameters of a statistical model, defined as follows: the likelihood of a set of parameter values given some observed outcomes is equal to the probability of those observed outcomes given those parameter values...

, AICc
Akaike information criterion
The Akaike information criterion is a measure of the relative goodness of fit of a statistical model. It was developed by Hirotsugu Akaike, under the name of "an information criterion" , and was first published by Akaike in 1974...

, and model's diagnosis.

Utilities

Interpolation
Interpolation
In the mathematical field of numerical analysis, interpolation is a method of constructing new data points within the range of a discrete set of known data points....

Functions - Flat forward/backward, linear, and cubic spline interpolation.
Time series Functions - Remove missing values from a time series.
Statistical Functions - Calculate the excess kurtosis of a GED and Student's t-dist.

Compatibility with Microsoft Excel

NumXL's statistical analysis software is compatible with all Excel versions from version 97 to version 2010, and is compatible with the Windows 9x till Windows 7 (32 and 64-bit) systems.

Release history

Version	Release name	Year	Release Date	Notes
NumXL	Alpha	2009	April 15, 2009
NumXL	Beta		June 30, 2009
NumXL	RC		July 24, 2009	Release Candidate.
NumXL 1.0	1.0		October 1, 2009	Official release of NumXL version 1.0.
NumXL 1.0	SP1	2010	January 5, 2010
NumXL 1.0	SP2		January 26, 2010
NumXL 1.0	SP3		September 2, 2010
NumXL 1.5	1.5	2011	June 13, 2011	Official release of NumXL 1.5.
NumXL 1.51	ORB	2011	September 23, 2011	Maintenance release.

External links

The source of this article is wikipedia, the free encyclopedia. The text of this article is licensed under the GFDL.