The history of least squares

Introduction History of the least squares method In 1801, the Italian astronomer Giuseppe Piazzi discovered the first asteroid Ceres. After 40 days of follow-up observations, due to the movement of Ceres

The history of least squares

In 1801, Italian astronomer Giuseppe Piazzi discovered the first asteroid Ceres. After 40 days of follow-up observations, Piazzi lost Ceres' position because Ceres moved behind the sun. Subsequently, scientists around the world began to search for Ceres using Piazzi's observational data, but based on most people's calculations, the search for Ceres yielded no results. Gauss, then aged 24, also calculated the orbit of Ceres. Austrian astronomer Heinrich Olbers rediscovered Ceres based on an orbit calculated by Gauss.

The least squares method used by Gauss was published in his 1809 book "On the Motion of the Celestial Bodies."

French scientist Legendre independently invented the “method of least squares” in 1806, but it remained unknown because it was not known to the whole world.

Legendre had a dispute with Gauss over who was the pfirst to create the principle of least squares.

In 1829, Gauss provided proof that the optimization effect of the least squares method is stronger than that of other methods, so it is called Gauss's theorem- Markov. (from wikipedia)

The role of the least squares method

Of course! If you like RPG games like "Heavy Soldiers", I can recommend several games in a similar style.

First of all, if you like the mecha fights in "Juggernaut", then the "Hearts of Iron" series might interest you. This game series is centered around mechas, and players can customize their mechas and engage in combat. These games usually have rich plots and strategic combat systems, allowing you to enjoy an in-depth role-playing experience.

Another game worth mentioning is the Final Fantasy series. Each game in this series has a unique storyline and charactersimpressive. The combat system is also excellent, combining turn-based and real-time elements. You can explore a huge world, fight a variety of enemies there and gradually improve your character's strength.

If you are interested in science fiction themes, you can try the “Fallout” series. This game series takes place in a world after a nuclear war. Players must survive in wastelands and fight against various enemies. There are rich tasks and plots in the game, allowing you to feel the real post-apocalyptic atmosphere.

Finally, I would also like to recommend a classic role-playing game, "The Witcher 3: Wild Hunt". The game is based on the series of novels by Polish writer Andrej Sepkovsky and tells the adventures of the protagonist Geralt. The game world is very large and full of various tasks, copies and characters. The combat system is in-depth and ininteresting, and the plot is exciting and exciting.

In short, if you like RPG games like "Heavy Soldiers", the games recommended above can bring you a similar gaming experience. I hope you find a game you like and have a great time playing it!

The least squares method has the effect of not only providing the results of data fitting, but also providing us with insights into the characteristics and patterns of the data .

The least squares method is a mathematical tool widely used in many disciplines such as error estimation, uncertainty, system identification and prediction, and data processing. data. In 1801, Italian astronomer Giuseppe Piazzi discovered the first asteroid, Ceres. After 40 days of follow-up observations, Piazzi lost Ceres' position because Ceres moved behind the sun.

Scientists around the world then began searching for Ceres using Piazzi's observational data, but based on most people's calculations, the search for Ceres yielded no results . Only the 24-year-old Gauss calculated Ceres' orbit, which was confirmed by the observations of Austrian astronomer Heinrich Olbers, allowing the astronomical community to predict Ceres' precise position.

The same method has also produced many astronomical achievements such as Halley's Comet. The method Gauss used was the method of least squares, published in his 1809 book “On the Motion of the Celestial Bodies.” In fact, the French scientist Legendre independently invented the least squares method in 1806, but it remained unknown because it was not known to the whole world.

The least squares method (also known as the least squares method) is a techniquethan mathematical optimization. It finds the best functional match of the data by minimizing the sum of squared errors. The least squares method can be used to easily obtain unknown data and minimize the sum of squared errors between the obtained data and the actual data.

Characteristics of the least squares estimator

Depending on the sample data, the parameter estimator of the simple linear regression model can be obtained using the least squares estimator. But how close are the estimator parameters to the true population parameters and whether there are other better estimators.

This involves the minimum (or best) variance (Best), linear (Linear) and unbiased (Unbiased) properties of the least squares estimator or estimator, called BLU characteristics. This is the main reason whyOrdinary least squares are widely used to estimate econometric models.

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