R programming Assignment Help

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Topics for Assignment help :

Predicting Algae Blooms

• Descriptive statistics
• Data visualization
• Strategies to handle unknown variable values
• Regression tasks
• Evaluation metrics for regression tasks

Predicting Algae Blooms

• Multiple linear regression
• Regression trees
• Model selection/comparison through k-fold cross-validation

Detecting Fraudulent Transactions

• Clustering methods
• Classification methods
• Imbalanced class distributions and methods for handling this type of problems
• Naive Bayes classifiers
• Precision/recall and precision/recall curves

Classifying Microarray Samples

• Feature selection methods for problems with a very large number of predictors
• Random forests
• k-Nearest neighbors

Statistical Computing Assignment help

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• Programming languages, data structures, programming using R, C/C++, and Perl, HTML and CGI., Calling C/C++ from R., Writing R extensions (called packages)., Grid graphics; interactive and dynamic graphics., Static and dynamic memory management
• numerical libraries and optimization in R, Parallel computing in R., Massive data challanges and solutions., Image processing., Hierarchical models., cluster analysis, Random Number Generation, Pseudo random numbers, linear congruential generator, properties of PRNGs, inverse transform method, basic rejection sampling, envelope rejection sampling, transformation of random variables.
• Monte Carlo Methods, Monte Carlo estimates, bias, mean square error, estimating probabilities, choice of sample size,, importance sampling, antithetic variables, variance reduction, applications in statistical inference, Markov Chain Monte-Carlo Methods, Markov Chains with discrete/continuous state space, random walk, transition matrices, transition densities, stationary distributions
• Metropolis-Hastings algorithm, convergence of MCMC methods,, burn-in period, application to Bayesian inference, MH with discrete state space, detailed balance condition, Metropolis algorithm, random-walk Metropolis, independence sampler., Bootstrap Methods, Empirical distributions, the bootstrap principle, bootstrap estimate for the bias,, bootstrap estimate of the standard error
• Introduction to statistical computing, Least squares (regression), Penalized and weighted least squares, Density estimation and smoothing, Matrix computations, Optimization (likelihood estimation), Newton-Raphson, Fisher scoring, Combinatorial optimization, Integration (probabilities), Quadrature, Laplace approximation, Resampling and Monte Carlo inferences, Jackknife and Bootstrap, Permutation procedures, Monte Carlo simulation, Statistical graphics

Stata Assignment Help

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Our online STATA assignment help tutors are available 24/7 for students struggling with complex STATA problems. Get the 24/7 help & complete solutions for STATA assignments . 

• Stata and data management
• Data visualisation through stata
• Analysing panel data in stata
• Visualizing regression models using stata
• Interpreting and Visualizing Regression Models Using Stata

Stata, as SPSS (Statistical Package for Social Science), is a broadly useful measurable programming package. It is command based software, and is accessible for Windows, Macintosh, and Linux frameworks. Stata gives an exceedingly adaptable intelligent mode that makes it less demanding for fledglings to learn and utilization. Stata likewise backings highlights for programming and network control. Stata has two essential menu tabs: Graphics and Statistics. Inside of "Insights" there are twenty-one sub tabs and various tabs inside of those tabs. Inside of "Representation" there are twenty-one tabs too. Stata performs most broad measurable investigations (relapse, logistic relapse, survival examination, investigation of change, variable examination, and some multivariate examination).

 

The best qualities of Stata are presumably in relapse (it has simple to utilize relapse analytic apparatuses), logistic relapse, (add on projects are accessible that extraordinarily streamline the translation of logistic relapse results, and ordinal logistic and multinomial logistic relapses are anything but difficult to perform). Stata additionally has an exceptionally decent exhibit of hearty systems that are anything but difficult to utilize, including strong relapse, relapse with powerful standard slips, and numerous other estimation orders incorporate vigorous standard mistakes also.

SAS Programming Assignment Help

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Our SAS Assignment help tutors help with Miner, Tree in SAS Enterprise Miner,A Decision Tree Model to Predict Response to Direct Marketing,Base SAS. Data Visualization, Enterprise Management.

• Accessing Data, Creating Data Structures, Managing Data, Generating Reports, Handling Errors, Accessing Data Using SQL, Macro Processing, Advanced Programming Techniques
• Clinical Trials Programming Using, SAS Advanced Analytics, Predictive Modeler Using SAS Enterprise Miner 13, SAS Business Intelligence and Analytics, SAS Data Management, Data Preparation, Predictive Models, Data splitting/balancing/overfitting/oversampling
• Logistic/linear regression, Artificial neural networks (MLP), Decision trees, Model Assessment, models/lift chart/ROC/profit & loss, Scoring and Implementation

SAS System integrates with many SAS business solutions that enable large scale software solutions for areas such as human resource management, financial management,business intelligence, customer relationship management , The SAS System (originally Statistical Analysis System) is an integrated system of software products provided by SAS Institute that enables the programmer to perform.

MATLAB Game Development Assignment Help

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2 Project Goal

The end-goal of the project is a native Android game application that runs on a mobile device, such as an iPhone, Android, Blackberry, Palm, Windows Mobile, etc. The goal is to design and implement a game that uses Android device features in an interesting and useful manner, provides a significant amount of functionality, and has some degree of polish. A portion of the project grade will be based on these criteria.

Mobile Device Features The game application should combine at least two, and preferably more, mobile device features, such as a camera, GPS, networking, accelerometers, Bluetooth, etc, in an interesting and useful manner. Device features vary from device to device, so an exhaustive list of options is not possible; check with the instructor if you are not sure about what counts for a feature.

Functionality

The game application should also provide some kind of interesting and useful functionality. This does not necessarily mean that you have to write a lot of code, but this is not expected to be a one weekend project either. The game application will likely have multiple views (screens), is expected to perform a runnable and fun game. That is, if no one would ever want to buy your application, even if it was free, then you may need to rethink your application.

You should be able to divide the functionality of your application into three distinct levels: Minimum Functionality: the minimum amount of functionality that you expect to implement, assuming all your carefully laid plans are disrupted, Expected Functionality: the functionality you expect to implement, assuming most things go according to plan, and Bonus Functionality: the functionality you would like to implement, assuming you managed to get everything done a lot earlier than expected. This is your opportunity to be really creative. In the project proposal you will describe what functionality your application will provide. Your project will be graded in part based on how much of your proposed functionality you accomplished. If you are not sure if you have too little or too much functionality, check with the instructor.

Computational Statistics Assignments help

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Our online assignment help tutors are available 24/7 for students struggling with complex Computational Statistics problems. Get the 24/7 help & complete solutions for Computational Statistics assignments. 

 Few topics for Computational Statistics coursework help:

• Modern computationally-intensive statistical methods
• Monte Carlo integration and simulation
• optimization and maximum likelihood estimation

Our online Computational Statistics experts help with complex questions, essays, report writing & case studies for guaranteed academic success.

Civil Engineering Assignment Experts

We offer excellent services for Civil Engineering Assignment help & Civil Engineering Homework help. Our Civil Engineering Online tutors are available for instant help for Civil Engineering assignments & problems.

Civil engineering is the study to plan, design, construct, supervise, manage, research & problem-solving skills to maintain sustainable built and natural environments or community infrastructure. It offers research, fostering innovative and creative solutions for our environment. It is the study of structures, geomechanics, fluids and complex systems, sustainability, climate change, water management and the natural environment & project management.

We help with coursework and research-orientated degrees in Civil engineering.

Our online Civil Engineering experts help with complex questions,  report writing & case studies for guaranteed academic success.

Our Civil Engineering University Assignment help section is for students.