Statistica的問題，透過圖書和論文來找解法和答案更準確安心。 我們找到下列懶人包和總整理

Statistical Learning and Modeling in Data Analysis: Methods and Applications

為了解決Statistica的問題，作者 這樣論述：

Simona Balzano is an Assistant Professor of Statistics at the University of Cassino and Southern Lazio, Italy, where she teaches on data analysis and research methods in management. Her recent research activities concern multivariate analysis, partial least squares regression and path-modeling, and

structural equation modeling. Her interests include applications in performance analysis, consumer analysis, and other related fields of business and industry.Giovanni C. Porzio is a Professor of Statistics at the University of Cassino and Southern Lazio, Italy, where he has previously served as Dep

artment Head and Director of Graduate Studies in Economics. His research interests include directional statistics, statistical learning, nonparametric multivariate analysis and data depth, graphical methods and data visualization. His research work has appeared in several journals and books.Renato S

alvatore is an Assistant Professor of Economic Statistics at the University of Cassino and Southern Lazio, Italy. He has co-authored papers, book chapters, and proceedings on sampling surveys, small area estimation, and multivariate analysis. In addition, he has been co-editor of several conference

proceedings, and currently teaches on economic statistics and market analysis.Domenico Vistocco is an Associate Professor of Statistics at the University of Naples Federico II, Italy. He is an Associate Editor of Computational Statistics and Editorial Manager of Statistica Applicata - Italian Journa

l of Applied Statistics. He has co-authored two books on quantile regression and ca. 100 papers, book chapters, proceedings, post-proceedings and editorials on various statistical topics. He teaches on statistical inference, data analysis, applied statistics and statistical programming. His research

interests include quantile regression, computational statistics, statistical models, exploratory data analysis and visualization.Maurizio Vichi is a Professor of Statistics and Chair of the Department of Statistical Sciences at Sapienza University of Rome, Italy. He is also Coordinating Editor of t

he international journal Advances in Data Analysis and Classification and Acting Chair of the European Statistical Advisory Committee of the EU. He teaches on multivariate statistics and data analysis and statistical modeling. His research interests include statistical models for clustering, classif

ication, dimensionality reduction, composite indicators, PLS, SEM and new methods for official statistics based on smart statistics and big data analysis. He is the author of more than 150 papers, mainly published in peer-reviewed international statistics journals.

Statistica進入發燒排行的影片

初級統計學：解開生活中的數字密碼(修訂二版)

為了解決Statistica的問題，作者呂岡玶,楊佑傑 這樣論述：

　　生活化 　　以生活案例切入，避開艱澀難懂的公式和符號，利用簡單的運算推導統計概念，最適合對數學不甚拿手的讀者。 　　直覺化 　　以直覺且淺顯的文字介紹統計的觀念，再佐以實際例子說明，初學者也能輕鬆理解，讓統計不再是通通忘記！ 　　應用化 　　以應用的觀點出發，讓讀者瞭解統計其實是生活上最實用的工具，可以幫助我們解決很多周遭的問題。統計在社會科學、生物、醫學、農業等自然科學，還有工程科學及經濟、財務等商業上都有廣泛的應用。

具有時間窗和自送選項的多場站垃圾收集車路線問題

為了解決Statistica的問題，作者Winy Fara Nadira 這樣論述：

Almost every activity that human do generates waste. To reduce the waste that keeps increasing due to the change of public consumption and lifestyle, a better waste management is needed. Poor waste management lead to health and environment problems, as well as climate change. As a pioneer of commun

ity-based establishment that aims to reduce the amount of recyclable house called Waste Bank Program, the performance of waste bank in Yogyakarta city is still underutilized. To increase community participation in depositing their waste to the waste bank, additional home pick-up service believed to

increase community participation in depositing their waste to a waste bank. As the result, a routing plan to visit and collect the resident’s waste is needed.In this research, we introduced a new extension of VRP called Multi-Depot Waste Collection Vehicle Routing Problem with Time Window and Self D

elivery Option (MDWCVRPTW-SDO) to address the problem. There are three types of residents considered in this research, i.e. residents who ask for pick-up service to deposit their waste, residents who drop-off their waste by themselves, and residents who are flexible in terms of two aforementioned me

thods. A simulated annealing (SA) heuristic is developed in this research to solve the MDWCVRPTW-SDO instances and compare the result with the best-known solution from the previous research. The result shows that the algorithm shows its robustness in terms of solution quality. Sensitivity analysis a

lso conducted in this research where the result shows that the selection of the appropriate compensation policy needs to be carefully thought out since it significantly affects the operational cost of MDWCVRPTW-SDO.