# Time Series Forecasting Model and its JAVA Implementation

Project Title: Time Series Forecasting Model and its JAVA Implementation

Primary Skill: Programming

Secondary Skill: Java

Additional Skills: Statistical algorithms for Time series model for forecasting the predictions based on large data are essential.

Project Description:

We need professional to develop the following Predictive model for modeling large data coming from Banking, finance, Insurance, Telecommunication and such other fields.

## Deliverables

Project Description: We need professional to develop the following Predictive model for modeling large data coming from Banking, finance, Insurance, Telecommunication and such other fields.

Time Series Forecasting Model:

The set up for developing Time series forecasting model is : One response variable measured on a time-scale with several predictor variables (may be continuous or categorical). Usually the data size is large and it will be stored in EXCEL or ASCII format. Assume that column represents a response variable while Rows indicate the cases.

Requirement #1

Develop a statistical algorithm for fitting and selecting ‘best’ ARIMA (p, d, q) (P,D,Q) _m [where m is the seasonal frequency] model to univariate time series consisting of one continuous response variable and several regressors (may be continuous or categorical). Assume that the input data is homoscedastic.

Write explicitly the computational steps involved in the fitting of the above model. Your algorithm steps should clearly indicate the tools used to handle large data. Provide details of iterative method that you are going to use to fit the model along with convergence criteria.

Develop a Java Code corresponding to the above algorithm.

Your program should not crash at extreme values or invalid input. Your code should have built-in checks to avoid crashes and or incorrect results. This has to be documented with suitable test cases.

Expected output: The output should produce best ARIMA model with estimated coefficients, p value, standard estimate of the coefficients and log likelihood according to either AIC, AICc or BIC value. The function should search over possible models within the specified Order (p, q, P, Q) constraints.

Using the final ‘best ‘model your program should generate forecast of response and confidence interval of the forecast value for specified period ahead.

Test case results to demonstrate how the program behaves at extreme values, Invalid inputs etc. Your program should work correctly for large data. Include at least one example to demonstrate working of the program.

Requirement #02

Your program should select a proper subset of predictors. It should also rank them as per their percentage of importance in the model.

Model Validation should be done and the output should indicate the prediction accuracy and test of white noise residuals of the fitted model.

Time Line: Time to develop a statistical algorithm and its Java implementation should not exceed Two months.

Budget: \$4000-\$ 6000

( 0 comentários ) United States

ID do Projeto: #3036718

## 12 freelancers estão ofertando em média \$3375 para esse trabalho

Wonderer

See private message.

\$4250 USD in 14 dias
(71 Comentários)
5.8
hamse001

See private message.

\$5100 USD in 14 dias
(10 Comentários)
5.8
homi12345

See private message.

\$3400 USD in 14 dias
(9 Comentários)
2.7
akmkat

See private message.

\$4250 USD in 14 dias
(2 Comentários)
2.5
jcentricity

See private message.

\$5100 USD in 14 dias
(2 Comentários)
2.5
chiru79850

See private message.

\$944.35 USD in 14 dias
(2 Comentários)
1.9
storchei

See private message.

\$510 USD in 14 dias
(2 Comentários)
0.9
lchzh

See private message.

\$3825 USD in 14 dias
(0 Comentários)
0.0
amitusaineu

See private message.

\$4360.5 USD in 14 dias
(0 Comentários)
0.0
melhorinfo

See private message.

\$4250 USD in 14 dias
(5 Comentários)
0.0
vw6976298vw

See private message.

\$425 USD in 14 dias
(0 Comentários)
0.0
maiphuongvw

See private message.

\$4080 USD in 14 dias
(2 Comentários)
2.3