R语言科学编程与模拟实战指南（第二版）

r语言
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"《Introduction to Scientific Programming and Simulation Using R（Second Edition）》是针对初学者的一本关于R语言科学编程和模拟的教材，由多位在统计学领域有深厚背景的专家编写，旨在深入解析R语言在统计计算和图形化方面的应用原理。本书是R系列的一部分，反映了R语言及其软件环境在学术研究、教育和工业领域的广泛使用，并随着持续的版本更新和超过5000个可用包的增长，成为了一个重要的编程工具。尽管R的文档在不断更新，但书籍仍然是系统学习R语言各个方面的宝贵资源，该系列图书致力于提供这样的平台，涵盖了R语言的开发和应用的多个方面，包括特定学科的应用。" 正文： 《Introduction to Scientific Programming and Simulation Using R》第二版是一本专为R语言初学者设计的教程，旨在教授如何利用R语言进行科学编程和模拟。R语言作为统计计算和数据可视化的首选工具，它的普及率和影响力日益增长。书中不仅涵盖了R语言的基础知识，还深入探讨了其在科学研究中的高级应用。 该书的作者阵容强大，包括斯坦福大学统计系的John M. Chambers、加州大学戴维斯分校统计系的Duncan Temple Lang、苏黎世大学生物统计学分部的Torsten Hothorn以及RStudio的Hadley Wickham。这些专家的贡献确保了教材的专业性和深度，他们结合各自的实践经验，为读者提供了全面而实用的学习材料。 书中“目标与范围”部分提到，R系列图书旨在跟上R语言快速发展的步伐，通过出版一系列书籍，覆盖R语言的开发、应用及特定学科的实践案例。这表明本书不仅关注R语言的基础编程技术，还将涉及到实际问题的解决策略，比如在生物统计学、社会科学或其他定量分析领域中的应用。 对于R语言的新手，本书将引导他们逐步理解R的语法结构，学习如何处理数据、创建统计模型和构建复杂的图形。此外，还会讲解如何利用R进行模拟，这是科学建模和预测分析中的关键技巧。通过模拟，读者可以更好地理解和预测复杂系统的行为。 书中将涵盖R语言的核心软件更新，以及数千个可用的扩展包，这些包极大地丰富了R的功能，使其能够处理各种各样的数据分析任务。此外，书中还可能涉及如何有效地利用R进行数据清洗、探索性数据分析、假设检验、机器学习等统计方法。 《Introduction to Scientific Programming and Simulation Using R》第二版是一本全面且深入的R语言学习资源，对于希望在科研和实践中掌握R语言的人来说，它既是入门的钥匙，也是进阶的阶梯。通过本书，读者不仅可以提升编程技能，还能了解到R语言在解决实际问题时的强大能力。

Introduction to Electronic Warfare Modeling and Simulation

2018-11-12 上传
Introduction_to_Electronic_Warfare_Modeling_and_Simulation

Introduction to Scientific Programming and Simulation Using R

2014-05-20 上传
r程序全面介绍 快速入门 非常经典的入门教材 引用率高

Introduction to Scientific Programming and Simulation Using R.

2018-04-14 上传
这是一本关于介绍语言的书籍，对于做数据挖掘的同学来说是一本入门教程，需要的下载

void be() { #ifdef SIMULATION AUV_R_Main_Init(); AUV_R_MAIN_DataInit(); AUV_R_Init_SIMU_NET(); AUV_R_WL_Com_Init(); FLSNId = taskSpawn("tFLSNNet", 102, VX_FP_TASK, 5000, (FUNCPTR)AUV_R_Init_FLSN_NET, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0); NetId = taskSpawn("tCtrlNet", 102, VX_FP_TASK, 5000, (FUNCPTR)AUV_T_Init_CTRL_NET, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0); #else AUV_R_Main_Init(); AUV_R_MAIN_DataInit(); AUV_R_Init_BCHECK_NET();/**/ AUV_R_BD1_Com_Init();/* */ /*AUV_R_GPS_NET_Init(); */ AUV_R_Init_IPS_NET(); AUV_R_INS_NET_Init();/**/ AUV_R_WL_Com_Init();/**/ AUV_R_4G_Com_Init(); AUV_R_ETC_NET_Init(); AUV_R_DVL__NET_Init(); FLSNId = taskSpawn("tFLSNNet", 102, VX_FP_TASK, 5000, (FUNCPTR)AUV_R_Init_FLSN_NET, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0); NetId = taskSpawn("tCtrlNet", 102, VX_FP_TASK, 5000, (FUNCPTR)AUV_T_Init_CTRL_NET, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0); #endif AUV_R_PreProcess_init(); AUV_R_DataProc_init(); AUV_R_Controller_Init(); AUV_R_PathPlan_Init(); }

2023-06-10 上传
这段代码看起来像是初始化某个系统或者应用程序。它使用了条件编译指令 #ifdef 和 ...最后，它调用了一些初始化函数，如 AUV_R_PreProcess_init，AUV_R_DataProc_init，AUV_R_Controller_Init 和 AUV_R_PathPlan_Init。

ERROR: cannot launch node of type [autolabor_simulation_stage/simulation_stage_node]: Cannot locate node of type [simulation_stage_node] in package [autolabor_simulation_stage]. Make sure file exists in package path and permission is set to executable (chmod +x)

2023-05-31 上传
这个错误可能是因为节点类型 `simulation_stage_node` 找不到。请确保你已经正确安装了 `autolabor_simulation_stage` 包并且已经编译。你可以尝试在终端中输入以下命令来编译该包： ``` cd <your_catkin_ws> ...

python dump_data.py [YOUR PATH]/Next_Generation_Simulation__NGSIM__Vehicle_Trajectories_and_Supporting_Data.csv这段代码什么用处

2023-02-12 上传
这段代码是在使用 Python 程序，用于将一个名为 "Next_Generation_Simulation__NGSIM__Vehicle_Trajectories_and_Supporting_Data.csv" 的 CSV 文件的数据转储（或称为导出）到一个指定的文件路径中。代码中的 `dump...

You could also create code to simulate the Monty Hall problem. Create a function named random_door, which uses numpy.random.choice to sample 1 door randomly from a list of integer door indices (1-3 in this case). Use this function to randomly select the door the car is behind and the contestant’s initial choice of doors. Create a function monty_choice, which chooses the door Monty opens, conditional on the contestant’s choice of doors and the door with the car. For the case where the contestant has selected the door with the car, select the door to open by simulating the flip of a fair coin using the np.random.binomial function with n = 1. Create a function win_car, which determines if the contestant wins the car, conditional on the strategy selected, {switch, noswitch}, the door the contestant selected, the door with the car, and the door Monty opened. Create a function named simulation that allows you to run the simulation n = 1000 times, with a switch or noswitch strategy. Execute your simulation for each possible strategy. For the two strategies, plot side by side bar charts showing the numbers of successes and failures for each strategy. Describe the strategy a contestant should adopt for this game. How much will the chosen strategy change the probability of winning a car? Is this result consistent with the conditional probability of this problem?

2023-06-09 上传
This code defines three functions: `random_door` to randomly select a door for the car or the contestant, `monty_choice` to choose the door Monty opens based on the contestant's choice and the ...

You could also create code to simulate the Monty Hall problem. 1. Create a function named random_door, which uses numpy.random.choice to sample 1 door randomly from a list of integer door indices (1-3 in this case). Use this function to randomly select the door the car is behind and the contestant’s initial choice of doors. 2. Create a function monty_choice, which chooses the door Monty opens, conditional on the contestant’s choice of doors and the door with the car. For the case where the contestant has selected the door with the car, select the door to open by simulating the flip of a fair coin using the np.random.binomial function with n = 1. 3. Create a function win_car, which determines if the contestant wins the car, conditional on the strategy selected, {switch, noswitch}, the door the contestant selected, the door with the car, and the door Monty opened. 4. Create a function named simulation that allows you to run the simulation n = 1000 times, with a switch or noswitch strategy. 5. Execute your simulation for each possible strategy. For the two strategies, plot side by side bar charts showing the numbers of successes and failures for each strategy. 6. Describe the strategy a contestant should adopt for this game. How much will the chosen strategy change the probability of winning a car? Is this result consistent with the conditional probability of this problem?

2023-06-09 上传
According to the simulation results, the contestant should switch doors to maximize their chances of winning the car. The switch strategy has a success rate of around 66.5%, while the no switch ...

module four_to_one_selector(input [3:0] data_in, input [1:0] sel, output reg data_out); wire w1, w2; // first 2-to-1 data selector // sel[0] controls which input is selected assign w1 = (sel[0] == 0) ? data_in[0] : data_in[1]; // second 2-to-1 data selector // sel[1] controls which input is selected assign w2 = (sel[1] == 0) ? data_in[2] : data_in[3]; // final output // sel[1] controls which input from the second selector is selected always @ (sel or data_in) case (sel) 2'b00: data_out = data_in[0]; 2'b01: data_out = data_in[1]; 2'b10: data_out = w1; 2'b11: data_out = w2; endcaseendmodule激励文件

2023-05-29 上传
// End simulation #10 $finish; end endmodule ``` 在这个例子中，我们首先定义了一个 `tb_four_to_one_selector` 模块，这个模块包含了一个四选一选择器的实例 `uut`，以及输入和输出信号。在 `initial` 块中...

Write the code about Process Scheduling Algorithm Simulation in C++.1、 Simulate the operation of the round-robin algorithm for process scheduling. 2、 Create at least 15 processes (using function fork())and output their scheduling situation under the scheduling algorithm mentioned above and output it to the terminal to check the execution of the algorithm. 3、 The output should include the arrival time of the processes, the end time, and the average execution time

2023-05-25 上传
Here is the code for process scheduling algorithm simulation using round-robin algorithm in C++: ``` #include #include #include #include using namespace std; struct process { int pid; int ...
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